Amar Choudhary

@alliance.edu.in

Assistant Professor, Departmet of Electronics and Communication Engineering
Alliance University

Amar Choudhary


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https://researchid.co/chitraansh

RESEARCH, TEACHING, or OTHER INTERESTS

Engineering, Engineering, Renewable Energy, Sustainability and the Environment, Artificial Intelligence
36

Scopus Publications

137

Scholar Citations

6

Scholar h-index

4

Scholar i10-index

Scopus Publications

  • New architectures to enable a holistic approach toward sustainable and intelligent agriculture applications
    Sammy Francis, Pankaj Goel, Mohammed Wasim Bhatt, Amar Choudhary, Kochumol Abraham, Aniruddha Shelotkar
    Robotics and Intelligent Machines in Smart Agriculture Emerging Systems and Applications, 2026
    Sustainable agriculture is important for solving the world’s problems of food security, climate change, and resource depletion. Artificial Intelligence (AI), combined with a series of emerging technologies, can be used to provide new solutions for boosting agricultural productivity with a neutral or positive impact on the environment. In this chapter, we provide new architectural templates that aim at allowing a holistic development of sustainable and AI-based applications for agriculture. It discusses the building blocks of IoT-enabled sensing systems, edge computing solutions for real-time decision-making, cloud-based big data analytics, and decision support systems augmented with AI and automation support with the use of robotics. Jointly, they allow precision agriculture, prophetic crop management, resource utilization, and even autonomous functioning. This chapter also focuses on integration approaches, including standardized communication protocols, modular system design, and security considerations, to make sure the system is interoperable and robust. It presents a collection of innovative works that address remote monitoring, control, and data acquisition, along with challenges of data security and privacy, through real-world applications, such as smart irrigation, automatic greenhouse control, and precision vineyard management, with successful implementations illustrating the enhanced plant yield and power consumption. It also discusses issues caused by data quality, computational limitations, resistance to the adoption of the system, and ethical considerations. Finally, the last section describes future perspectives on improving AI-based agricultural systems for larger applications. All in all, this architectural viewpoint can help architect such sustainable, intelligent, and efficient farming ecosystems.
  • Network Slicing Concurrent Resource Allocation for Improving Service Response of 6G Network Using a Novel Cycle-Consistent Spatial Frequency Self-Attention Network With Tasmanian Devil Optimization
    C. Sharanya, M. Prasanna Lakshmi, P. S. Velumani, Subhadra Perumalla, S. Lakshmanaprakash, Mahendra T. Jagtap, Amar Choudhary, Parameswaran Ramesh
    International Journal of Communication Systems, 2025
    In order to enhance resource use and service reliability for 6G users connected via Network‐in‐a‐Box (NIB) architectures, a DL‐based slicing‐dependent sequential resource distribution technique is presented in the proposed study. The central idea of the method is to create a Cycle‐Consistent Spatial Frequency Self‐Attention Network (CCSFSAN) and then use the Tasmanian Devil Optimization (TDO) algorithm to fine‐tune its hyperparameters. Then, to facilitate accurate network slicing and effective resource allocation, these optimized network instances are utilized by CCSFSAN. The resulting deep learning architecture, to fulfill the needs of 6G‐NIB communication networks, provides highly reliable, low‐latency, and energy‐efficient resource management. The performance evaluating metrics such as capacity, response ratio, latency, energy efficiency, blocking rate, and resource consumption are carefully examined in order to estimate the efficiency of the suggested resource allocation model. The outcomes show how well the proposed model works in the 6G environment to achieve better resource assigning and improved network performance. The developed model offers higher efficiency than the state‐of‐the‐art models by providing a high accuracy of 99.7%, increased capacity of 150 bits/s/Hz, high response ratio of 92%, better resource utilization of 0.94%, less blocking rate of 0.01, and less latency of 40 ms.
  • 5G Macro Cell Deployment in mmWave: A Case Study
    Amar Choudhary, Rakshita Mahadev Nyamagoudar, Babitha H T, Nabipatel Saidapur
    2025 IEEE International Conference on Advanced Computing Technologies Icact 2025, 2025
    With the rapid growth in telecom users across the globe, the telecom generations are evolving from 1G to 5G to meet the increasing demand without compromising with QoS. For this, naturally, optimal utilization of BW is observed. Along with this, the researchers are exploring the possibilities of the utilization of mmWave and THz wave to meet the increasing demand (without compromising with QoS). The proper placement of micro and macro cells are one of the supporting factors to meet this increasing demand of users. In this paper, we go for the deployment of micro cells for a particular locality by analysing its effectiveness. In this deployment the SINR values along with other QoS parameters are going to be compromised. The simulation is carried out in MATLAB 2024b. After simulation, we found that for this locality, the optimal coverage distance was only 566.1975 m. This work may be extended for the LoS (line of site) mapping and RF planning for a geographical aera of interest.
  • Smart Surveillance System for Accident Monitoring
    Amar Choudhary, Niveditha A, Madhumala Singh, Syed Khaja Mohiddin
    Proceedings of the 4th International Conference on Intelligent Computing Information and Control Systems Icoiics 2025, 2025
    With the quick pace of life today, real-time monitoring and response for incidents is a top priority, particularly for road safety and public security. Smart Surveillance is an AI-based, low-cost system for detecting, recording, and reporting accidents or suspicious activity. It employs a Raspberry Pi with a PiCamera to observe an area, and a trained ML model to identify anomalies. Upon detection, it takes a photo, sends alarms through GSM, and saves data on Firebase. The system operates over Wi-Fi, hosted on AWS Ubuntu to be scalable. Pre-processing and classification improve detection and minimize false alarms. Outcomes indicate high accuracy and response time compared to conventional systems, with enhanced automation and mobility.
  • AI/ML Applications in Spoofing Detection in 5G Networks: Challenges and Solutions
    Monika Singh, Raveesh Hegde, Mahesh Kumar Jha, Amar Choudhary, Rubini P
    Proceedings of the 3rd International Conference on Intelligent and Innovative Technologies in Computing Electrical and Electronics Iitcee 2025, 2025
    5G networks has advanced connectivity, high data, low latency and reliability. Along with these features new challenges come with respect to security, particularly spoofing attacks. One of the necessity in 5G and future wireless communication is to prevent the spoofing attacks depending on the applications. Artificial Intelligence (AI) and Machine Learning (ML) present promising solutions for detecting and mitigating spoofing threats in 5G networks. This paper explains the different types of spoofing and applications, challenges, and future prospects of AI/ML in addressing spoofing in 5G networks. AI/ML algorithms can be used in detection of the location of attackers. This paper also analyses current methodologies, highlight key challenges, and discuss potential advancements that could enhance the security of 5G networks.
  • Embracing the Future of Cybersecurity with Artificial Intelligence and Machine Learning
    Mahesh Kumar Jha, Raveesh Hegde, Monika Singh, Rubini P, Amar Choudhary
    Proceedings of the 1st IEEE International Conference on Advances in Next Gen Computer Science Icancs 2025, 2025
    As the number of cyber-attacks and data breaches are increasing day by day hence, cybersecurity retains a critical concern for every individual, businessman, and government servants. As a result, there is an urgent need for more efficient and effective cybersecurity measures. One promising approach is the application of AI/ML techniques in cybersecurity. This article aims to investigate the potential of AI and ML in enhancing cybersecurity. Specifically, the paper will investigate how AI can be used for threat detection and response, the advantages of using ML techniques for anomaly detection, and how AI/ML can improve the efficiency of cybersecurity operations. By examining these areas, this article seeks to give insights into how AI and ML may be leveraged to improve cybersecurity and safeguard against cyber threats.
  • Deep Learning-Based Diagnosis System for Liver Cancer Through Multimodal Determination for Early Treatment
    N. Sabiyath Fatima, Ramendra Singh, Akuthota Swathi, Amar Choudhary, Azhar Ahmed, Chhaya Sharma
    Proceedings of the 2024 International Conference on Artificial Intelligence and Emerging Technology Global AI Summit 2024, 2025
    The present research provides an analysis of the development and implementation of a deep learning-based diagnosis system for liver cancer. The provided system was developed using a dataset encompassing 2300 sensor readings, including imaging, clinical, and genomic data. A range of deep learning features was implemented to improve the early detection of liver cancer such as CNN, VGG 16, VGG 19, and Inception V3. The data were divided into two categories: one is for training, and another used for testing. The results of the data analysis have shown that VGG 19 provides the highest diagnostic accuracy of 98.76%, with VGG 16, Inception V3 and CNN displaying the levels of 94.5%, 93.4%, and 90.25%, respectively. The Model performance analysis was also augmented at the application of precision, recall, and F1 score indicators, as well as using AUC-ROC values which highlighted VGG 19 as the most effective algorithm. Another method of evaluation was the application of confusion matrices for plotting the results based on the number of true positive, true negative, false positive, and false negative detections, where all the samples from the dataset were added to each model calculation. The obtained results have shown the importance of multimodal data for the increase of diagnosis accuracy and revealed the promising potential of advanced computation techniques in medical analytics. In such a way, it can be stated that the developed deep learning models contribute to the ability of healthcare specialists in the definition of liver cancer at early stages, which allows timely interventions and facilitates the development of a range of personalized treatment protocols. The application of such algorithms has the potential to reshape liver cancer diagnostics, where major tasks are associated with further improvement and validation of the developed algorithms based on clinical case studies.
  • Wireless Sensor Networks (WSNs)-Integrated Machine Learning Algorithms for Water Resource Management
    Ashay Devidas Shende, J. Bibiana Jenifer, Gururaj L. Kulkarni, Amar Choudhary, Aparajita Mukherjee, Sampath Boopathi
    Enhancing Data Driven Electronics Through Iot, 2025
    The integration of Wireless Sensor Networks (WSNs) with advanced machine learning algorithms is revolutionizing water resource management. This chapter delves into the synergistic application of these technologies to address critical challenges in monitoring and managing water resources. It begins with an introduction to WSN technology, emphasizing its role in real-time data collection for water quality monitoring, irrigation systems, and flood detection. The chapter then explores various machine learning algorithms, such as Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), highlighting their applications in predictive analytics and anomaly detection. The chapter discusses successful implementations of WSNs and machine learning in water distribution and proactive infrastructure maintenance, emphasizing the importance of accurate data interpretation for informed decision-making in real-time data analysis techniques.
  • Classification and Detection of Prostate Cancer Using Machine Learning Techniques
    D. Vetrithangam, Pramod Kumar, Shaik Munawar, Rituparna Biswas, Deependra Pandey, Amar Choudhary
    Natural Language Processing for Software Engineering, 2025
    Carcinoma is a significant contributor to the death rates of individuals. Reducing the amount of time it takes to diagnose a patient is very necessary to improve their prognosis. Diagnostic imaging and other traditional methods are used by highly trained medical professionals to identify any telltale indicators that may be present in the bodies of their patients. In spite of the abundance of medical imaging data, manual diagnosis may still be subjective and time-consuming due to the fact that people's perceptions differ so much from one another. One of the primary reasons for the variability is the collecting of data from medical imaging. A proper diagnosis may be more difficult to get as a result of this. When performing activities such as machine learning and the processing of complex pictures, it is important to make use of the most advanced computational power available. Ever since the 1980s, there has been a persistent effort to develop a computer-aided diagnostic system that has the potential to help in the early diagnosis of a wide variety of malignancies. According to the most recent estimates, around one- seventh of men will be diagnosed with prostate cancer at some point in their life. This illness claims the lives of so many men every year, and it is unbearable that the number of men who are diagnosed with prostate cancer continues to climb. It is a tragedy that this number continues to rise. A powerful diagnostic system that is capable of managing high-resolution, multi-dimensional MRI images is an absolute need, in addition to computer-aided design (CAD) software. In the present moment, I am focusing my attention on a project that will make it easier for us to achieve our shared goals. Scientists are now studying methods to improve the speed, accuracy, and precision of computer-aided design (CAD) technology since it has been shown to be valuable. CAD technology has been demonstrated to be effective, as shown by the evidence. The development of techniques for the diagnosis and classification of prostate cancer via the use of MRI image processing and machine learning is the fundamental objective of this study as well.
  • A machine learning-based predictive model for drug sensitivity in breast cancer using gene expression data
    N. Noor Alleema, Amar Choudhary, Siddhi Nath Rajan, Rakesh Kancharla, Rakshit Kothari, Rakesh Kumar
    Blockchain and Iot Approaches for Secure Electronic Health Records Ehr, 2024
    Through the combination of tool learning patterns, this study offers a novel strategy for personalised treatment for the majority of breast malignancies. The authors used a carefully assembled dataset that included 3444 cases of drug management data, affected person profiles, diagnostic scans, and scientific reviews to train artificial neural networks (ANN), support vector machines (SVM), decision trees (DT), and random forests (RF) for drug sensitivity prediction modelling. While SVM demonstrated its capacity to handle high-dimensional statistics with an accuracy of 96.5%, the artificial neural network (ANN) exhibited remarkable versatility, achieving a commendable accuracy rate of 97.5%. The interpretability inherent in decision trees (DT) and the combined energy of random forests (RF) added crucial elements to the multifaceted methodology. The outcome of the research underscores that the proposed machine learning model stands out with the highest efficacy in predicting the most accurate drug for a given patient.
  • Coverage Analysis of 5G mmWave Base Station: A Case Study
    Amar Choudhary, Geetika Srivastava
    2024 International Conference on Recent Innovation in Smart and Sustainable Technology Icrisst 2024, 2024
  • Secured Data Transfer for Wireless Sensor Networks Using Homomorphic Cryptosystem
    Mahesh Kumar Jha, Rubini P, Amar Choudhary
    2024 International Conference on Recent Innovation in Smart and Sustainable Technology Icrisst 2024, 2024
  • Technicalities of O-RAN for 5G and B5G
    Amar Choudhary, Geetika Srivastava, Mahesh Kumar Jha
    2024 International Conference on Knowledge Engineering and Communication Systems Ickecs 2024, 2024
  • Facial Recognition based Attendance system using Machine Learning Models
    Amar Choudhary, B. Manimaran, Jeethendra Gouda G
    IEEE International Conference on Signal Processing and Advance Research in Computing Sparc 2024, 2024
  • Energy Management of Base Station in 5G and B5G: Revisited
    Amar Choudhary, Gaurav Kumar, Sandeep Dhariwal, Geetika Srivastava
    2024 International Conference on Knowledge Engineering and Communication Systems Ickecs 2024, 2024
  • Automated Robot with UV-C Sterilizer for Disinfection of Public Places
    Amar Choudhary, Doddamreddy Vishnu Vardhan, B. Madhu Sudhan, Devireddy Vineetha
    IEEE International Conference on Signal Processing and Advance Research in Computing Sparc 2024, 2024
  • Design and Development of Automatic Sanitization Solution for Human Being in Real World Scenario
    Taiba Ali, Monika Singh, Raveesh Hegde, Amar Choudhary, Anindrita Sen
    IEEE International Conference on Signal Processing and Advance Research in Computing Sparc 2024, 2024
  • Analyzing the Performance of Conformable and Non-Conformable Patch Antennas
    Sandeep Dhariwal, Vijay Kumar Lamba, Jyotirmoy Pathak, Amar Choudhary, Gaurav Kumar
    2024 5th International Conference for Emerging Technology Incet 2024, 2024
  • Deep Learning-Based ECG Analysis for Anomaly Detection and Classification Using DCNN
    Moghal Yaseen Pasha, Nitin Sharma, Priyanka, Vipul Kumar Verma, Amar Choudhary, Rahul Sharma
    Proceedings of International Conference on Emerging Technologies and Innovation for Sustainability Emergin 2024, 2024
  • IoT-Enabled Health Monitoring System for Safeguarding Vital Organs with Cloud-Based Diagnosis and Advanced Algorithms
    Salman Khursheed Ahmad, Km Ikra, Preeti Sharma, Yogita Kaushik, Amar Choudhary, Pradeep Kumar Tripathi
    2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2024, 2024
  • Transforming Business Management Practices for Increased Production Through Deep Learning and Cloud Computing Integration
    Namita Nath, Susmi Biswas, Roshini L, Deepika Bansal, Amar Choudhary, Mandeep Singh
    Proceedings of the 2024 International Conference on Artificial Intelligence and Emerging Technology Global AI Summit 2024, 2024
  • Retraction Notice: IoT-Enabled Health Monitoring System for Safeguarding Vital Organs with Cloud-Based Diagnosis and Advanced Algorithms (2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024 DOI: 10.1109/ICACITE60783.2024.10617208)
    Salman Khursheed Ahmad, Km Ikra, Preeti Sharma, Yogita Kaushik, Amar Choudhary, Pradeep Kumar Tripathi
    2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2024, 2024
  • Security and Threats in Aviation: Cryptographic Based Network Security System
    S. Harsha Vardhan, Mahesh Kumar Jha, Raveesh Hegde, Monika Singh, P. Rubini, Amar Choudhary
    IEEE International Conference on Signal Processing and Advance Research in Computing Sparc 2024, 2024
  • Transforming Business Management Practices for Increased Production through Deep Learning and Cloud Computing integration
    P. Santhosh Kumar, Anupam Singh, Soniya, Shaik Farhana, Amar Choudhary, Susmi Biswas
    2024 4th International Conference on Advancement in Electronics and Communication Engineering Aece 2024, 2024
  • Machine Learning-Based Optimization for Identifying Effective Drugs in Breast Cancer on an in Vitro Platform
    Mahima Saxena, P v v s Eswara Rao, Amar Choudhary, P. Srinivas Reddy, Vipin Kumar Sharma, Vinish Kumar
    2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2024, 2024
  • Advancements in Brain Disease Diagnosis for Comparing Traditional Methods and Deep Learning Approaches in Medical Imaging
    Sunita Kumari, Laxman Singh, Moghal Irfan Pasha, M. Kumaraswamy, Amar Choudhary, Monika Agarwal
    Proceedings of International Conference on Emerging Technologies and Innovation for Sustainability Emergin 2024, 2024
  • DEVELOPMENT OF MACHINE LEARNING BASED EMPIRICAL MODEL FOR ESTIMATION OF SOLAR RADIATION
    Journal of Theoretical and Applied Information Technology, 2023
  • A Novel Development of Blockchain based Messaging Application
    Deependra Pandey, Rohan Raj Gupta, Amar Choudhary
    IEEE International Conference on Advances in Electronics Communication Computing and Intelligent Information Systems Icaecis 2023 Proceedings, 2023
  • A Review for the Development of ANN Based Solar Radiation Estimation Models
    Amar Choudhary, Deependra Pandey, Saurabh Bhardwaj
    Smart Innovation Systems and Technologies, 2021
  • An Artificial Neural Network Based Approach of Solar Radiation Estimation Using Location and Meteorological Details
    Amar Choudhary, Deependra Pandey, Saurabh Bhardwaj
    Lecture Notes in Electrical Engineering, 2021
  • Global Solar Radiation Estimation Modeling Using Artificial Neural Network: A Case Study on Metro Cities of India
    Amar Choudhary, Deependra Pandey, Saurabh Bhardwaj
    Lecture Notes in Electrical Engineering, 2021
  • Analysis and Study of Solar Radiation Using Artificial Neural Networks
    Deepa Rani Yadav, Deependra Pandey, Amar Choudhary, Mihir Narayan Mohanty
    Smart Innovation Systems and Technologies, 2021
  • Recent developments in estimation of solar radiation
    Amar Choudhary, Deependra Pandey, Saurabh Bhardwaj
    2020 IEEE International Conference on Computing Power and Communication Technologies Gucon 2020, 2020
  • Artificial Neural Networks Based Solar Radiation Estimation using Backpropagation Algorithm
    International Journal of Renewable Energy Research, 2020
  • Overview of solar radiation estimation techniques with development of solar radiation model using artificial neural network
    Amar Choudhary, Deependra Pandey, Saurabh Bhardwaj
    Advances in Science Technology and Engineering Systems, 2020
  • A Review of Various Techniques for Solar Radiation Estimation
    Amar Choudhary, Deependra Pandey, Anil Kumar
    2019 3rd International Conference on Recent Developments in Control Automation and Power Engineering Rdcape 2019, 2019

RECENT SCHOLAR PUBLICATIONS

  • Smart Surveillance System for Accident Monitoring
    A Choudhary, A Niveditha, M Singh, SK Mohiddin
    2025 International Conference on Intelligent Computing, Information and … , 2025
    2025
  • Embracing the Future of Cybersecurity with Artificial Intelligence and Machine Learning
    MK Jha, R Hegde, M Singh, A Choudhary
    2025 International Conference on Advances in Next-Gen Computer Science … , 2025
    2025
  • 5G Macro Cell Deployment in mmWave: A Case Study
    A Choudhary, RM Nyamagoudar, N Saidapur
    2025 IEEE International Conference on Advanced Computing Technologies (ICACT … , 2025
    2025
  • Classification and Detection of Prostate Cancer Using Machine Learning Techniques
    D Vetrithangam, P Kumar, S Munawar, R Biswas, D Pandey, ...
    Natural Language Processing for Software Engineering, 29-41 , 2025
    2025
    Citations: 2
  • AI/ML Applications in Spoofing Detection in 5G Networks: Challenges and Solutions
    M Singh, R Hegde, MK Jha, A Choudhary
    2025 International Conference on Intelligent and Innovative Technologies in … , 2025
    2025
    Citations: 1
  • Wireless Sensor Networks (WSNs) integrated Machine Learning Algorithms for Water Resource Management
    SB Ashay Devidas Shende, Bibiana Jenifer J, Gururaj L. Kulkarni, Amar ...
    Enhancing Data-Driven Electronics Through IoT, 658 , 2025
    2025
    Citations: 1
  • Network Slicing Concurrent Resource Allocation for Improving Service Response of 6G Network Using a Novel Cycle-Consistent Spatial Frequency Self-Attention Network With …
    PR C. Sharanya, M. Prasanna Lakshmi, P. S. Velumani, Subhadra Perumalla, S ...
    International Journal of Communication Systems 38 (12) , 2025
    2025
    Citations: 1
  • Advancements in Brain Disease Diagnosis for Comparing Traditional Methods and Deep Learning Approaches in Medical Imaging
    S Kumari, L Singh, MI Pasha, M Kumaraswamy, A Choudhary, M Agarwal
    2024 International Conference on Emerging Technologies and Innovation for … , 2024
    2024
    Citations: 1
  • Deep Learning-Based ECG Analysis for Anomaly Detection and Classification Using DCNN
    MY Pasha, N Sharma, VK Verma, A Choudhary, R Sharma
    2024 International Conference on Emerging Technologies and Innovation for … , 2024
    2024
    Citations: 3
  • Transforming Business Management Practices for Increased Production through Deep Learning and Cloud Computing integration
    PS Kumar, A Singh, S Farhana, A Choudhary, S Biswas
    2024 4th International Conference on Advancement in Electronics … , 2024
    2024
  • Design and Development of Automatic Sanitization Solution for Human Being in Real World Scenario
    T Ali, M Singh, R Hegde, A Choudhary, A Sen
    2024 International Conference on Signal Processing and Advance Research in … , 2024
    2024
    Citations: 1
  • Facial Recognition based Attendance system using Machine Learning Models
    A Choudhary, B Manimaran, J Gouda
    2024 International Conference on Signal Processing and Advance Research in … , 2024
    2024
  • Security and Threats in Aviation: Cryptographic Based Network Security System
    SH Vardhan, MK Jha, R Hegde, M Singh, P Rubini, A Choudhary
    2024 International Conference on Signal Processing and Advance Research in … , 2024
    2024
  • Automated Robot with UV-C Sterilizer for Disinfection of Public Places
    A Choudhary, DV Vardhan, BM Sudhan, D Vineetha
    2024 International Conference on Signal Processing and Advance Research in … , 2024
    2024
    Citations: 1
  • Deep Learning-Based Diagnosis System for Liver Cancer Through Multimodal Determination for Early Treatment
    NS Fatima, R Singh, A Swathi, A Choudhary, A Ahmed, C Sharma
    2024 International Conference on Artificial Intelligence and Emerging … , 2024
    2024
  • Transforming Business Management Practices for Increased Production Through Deep Learning and Cloud Computing Integration
    N Nath, S Biswas, D Bansal, A Choudhary, M Singh
    2024 International Conference on Artificial Intelligence and Emerging … , 2024
    2024
  • Analyzing the Performance of Conformable and Non-Conformable Patch Antennas
    S Dhariwal, VK Lamba, J Pathak, A Choudhary, G Kumar
    2024 5th International Conference for Emerging Technology (INCET), 1-5 , 2024
    2024
    Citations: 1
  • Retraction Notice: IoT-Enabled Health Monitoring System for Safeguarding Vital Organs with Cloud-Based Diagnosis and Advanced Algorithms
    SK Ahmad, K Ikra, P Sharma, Y Kaushik, A Choudhary, PK Tripathi
    2024 4th International Conference on Advance Computing and Innovative … , 2024
    2024
  • Machine Learning-Based Optimization for Identifying Effective Drugs in Breast Cancer on an In Vitro Platform
    M Saxena, A Choudhary, PS Reddy, VK Sharma, V Kumar
    2024 4th International Conference on Advance Computing and Innovative … , 2024
    2024
    Citations: 6
  • Automated Robot with Uv-C Sterilizer
    D Vineetha, D Vishnuvardhan Reddy, A Choudhary
    Alliance College of Engineering and Design, Alliance University , 2024
    2024

MOST CITED SCHOLAR PUBLICATIONS

  • Artificial neural networks based solar radiation estimation using backpropagation algorithm
    A Choudhary, D Pandey, S Bhardwaj
    International Journal of Renewable Energy Research (IJRER) 10 (4), 1566-1575 , 2020
    2020
    Citations: 23
  • Technicalities of O-RAN for 5G and B5G
    A Choudhary, G Srivastava, MK Jha
    2024 International Conference on Knowledge Engineering and Communication … , 2024
    2024
    Citations: 18
  • A review of various techniques for solar radiation estimation
    A Choudhary, D Pandey, A Kumar
    2019 3rd International Conference on Recent Developments in Control … , 2019
    2019
    Citations: 15
  • Overview of solar radiation estimation techniques with development of solar radiation model using artificial neural network
    A Choudhary, D Pandey, S Bhardwaj
    Development 33, 37 , 2020
    2020
    Citations: 12
  • Global solar radiation estimation modeling using artificial neural network: a case study on metro cities of India
    A Choudhary, D Pandey, S Bhardwaj
    Intelligent Computing in Control and Communication: Proceeding of the First … , 2021
    2021
    Citations: 9
  • A review of potential, generation and factors of solar energy
    D Pandey, A Choudhary
    Journal of Thermal Engineering and Applications 5 (2), 1-4 , 2018
    2018
    Citations: 8
  • Machine Learning-Based Optimization for Identifying Effective Drugs in Breast Cancer on an In Vitro Platform
    M Saxena, A Choudhary, PS Reddy, VK Sharma, V Kumar
    2024 4th International Conference on Advance Computing and Innovative … , 2024
    2024
    Citations: 6
  • A novel development of blockchain based messaging application
    D Pandey, RR Gupta, A Choudhary
    2023 International Conference on Advances in Electronics, Communication … , 2023
    2023
    Citations: 5
  • A Review for the Development of ANN Based Solar Radiation Estimation Models
    A Choudhary, D Pandey, S Bhardwaj
    Intelligent and Cloud Computing: Proceedings of ICICC 2019, Volume 1, 59-66 , 2020
    2020
    Citations: 5
  • All about solar energy
    A Choudhary
    Int. J. Sci. Res. Develop. 5 (9), 708-711 , 2017
    2017
    Citations: 4
  • Deep Learning-Based ECG Analysis for Anomaly Detection and Classification Using DCNN
    MY Pasha, N Sharma, VK Verma, A Choudhary, R Sharma
    2024 International Conference on Emerging Technologies and Innovation for … , 2024
    2024
    Citations: 3
  • Artificial neural network based solar radiation estimation: a case study of Indian cities
    A Choudhary, D Pandey, S Bhardwaj
    Int. J. Emerg. Technol 11 (4), 257-262 , 2020
    2020
    Citations: 3
  • A Review of Semiconductor Solar PV Cell and Development of Solar Radiation Estimation Models
    D Pandey, A Choudhary
    Journal of Semiconductor Devices and Circuits 5 (1), 20-26 , 2018
    2018
    Citations: 3
  • Classification and Detection of Prostate Cancer Using Machine Learning Techniques
    D Vetrithangam, P Kumar, S Munawar, R Biswas, D Pandey, ...
    Natural Language Processing for Software Engineering, 29-41 , 2025
    2025
    Citations: 2
  • Energy Management of Base Station in 5G and B5G: Revisited
    A Choudhary, G Kumar, S Dhariwal, G Srivastava
    2024 International Conference on Knowledge Engineering and Communication … , 2024
    2024
    Citations: 2
  • Coverage Analysis of 5G mmWave Base Station: A Case Study
    A Choudhary, G Srivastava
    2024 International Conference on Recent Innovation in Smart and Sustainable … , 2024
    2024
    Citations: 2
  • Development of machine learning based empirical model for estimation of solar radiation
    S Mishra, D Pandey, S Bhardwaj, A Choudhary
    Journal of Theoretical and Applied Information Technology 101 (5), 1771-1783 , 2023
    2023
    Citations: 2
  • An artificial neural network based approach of solar radiation estimation using location and meteorological details
    A Choudhary, D Pandey, S Bhardwaj
    Applications of Artificial Intelligence and Machine Learning: Select … , 2021
    2021
    Citations: 2
  • Analysis and Study of Solar Radiation Using Artificial Neural Networks
    DR Yadav, D Pandey, A Choudhary, MN Mohanty
    Intelligent and Cloud Computing: Proceedings of ICICC 2019, Volume 1, 67-77 , 2020
    2020
    Citations: 2
  • Recent developments in estimation of solar radiation
    A Choudhary, D Pandey, S Bhardwaj
    2020 IEEE International Conference on Computing, Power and Communication … , 2020
    2020
    Citations: 2