Cross-Platform Multimodal Frogeye Leaf Spot Recognition and Classification: Advancing with Cutting-Edge CNN Technologies and Transfer Learning in Diverse Plant Species G. Mohan, R Usharani, Vatsala Tomar, Arthi A, Suniti Kumar Kuriyal, et al. Proceedings of International Conference on Circuit Power and Computing Technologies Iccpct 2024, 2024 Frogeye Leaf Spot, a common agricultural disease, poses a significant threat to crop yields. Using multimodal data from different platforms successfully has been a hurdle for existing research in leaf spot detection. Using cutting-edge convolutional neural network (CNN) and transfer learning techniques, this research presents a Cross-Platform Multimodal Recognition system to solve this issue. With a recall of 0.88, F1-score of 0.90, accuracy of 0.91, and precision of 0.92, the suggested method demonstrates exceptional performance. Our accuracy is 6% higher, F1-score is 8% higher, and recall is 9% higher than the preceding state-of-the-art, according to comparisons with previous studies. Improved Frogeye Leaf Spot detection on many platforms is a direct result of our method's success in combining picture and sensor data. This study improves farmers' ability to identify diseases and provides a solid answer for precision agriculture. Our Cross-Platform Multimodal Recognition system has shown to be effective in enhancing agricultural disease recognition, and the shown advances highlight its potential influence on crop management tactics.
Soil Health Intelligence System using Multispectral Imaging and Advanced Deep Learning Techniques (SHIDS-ADLT) B. Dhanalakshmi Communications on Applied Nonlinear Analysis, 2024 The Soil Health Intelligence System using Multispectral Imaging and Advanced Deep Learning Techniques (SHIDS-ADLT) is a cutting-edge solution designed to revolutionize the assessment and management of soil health. By leveraging the power of multispectral imaging, this system captures high-resolution data across various wavelengths, providing a comprehensive view of soil properties. Advanced deep learning algorithms are then applied to analyze this data, identifying patterns and insights that are not discernible through traditional methods. This integration of multispectral imaging with deep learning enhances the accuracy and efficiency of soil health monitoring, enabling precise identification of nutrient deficiencies, soil contamination, and other critical parameters that affect agricultural productivity.SHIDS-ADLT offers a scalable and user-friendly platform for farmers, agronomists, and researchers, facilitating informed decision-making and sustainable agricultural practices. The system’s ability to provide real-time analysis and actionable recommendations ensures that soil health is maintained at optimal levels, promoting higher crop yields and reducing the reliance on chemical fertilizers. Moreover, the continuous monitoring capabilities of SHIDS-ADLT help in early detection of soil degradation, allowing for timely interventions. This innovative approach to soil health management represents a significant advancement in agricultural technology, supporting the goal of achieving food security and environmental sustainability.
A Novel Q-Learning Optimization Approach for Flight Path Prediction in Asian Cities Keshavagari Smithin Reddy, B Natarajan, Arthi A, M Tamilselvi, Sridevi R 2023 3rd Asian Conference on Innovation in Technology Asiancon 2023, 2023 The domains of logistics and transportation have long been interested in the optimization of flight paths between cities. This research aims to use Skyscanner data to estimate the optimal flight path between 42 Asian destination cities using Reinforcement Learning (RL) techniques, notably Q-learning. RL is a great strategy for addressing the Travelling Salesman Problem (TSP) connected to aircraft route optimization because of the distinctive reward structure it provides. The main objective of the proposed research is to create a model that learns to suggest aircraft routes based on factors such as cost, time, and number of intermediate points that maximize benefits. The proposed research work incorporates a novel Q-learning approach for training an RL agent to predict optimal flight paths. The proposed research work showcases the power-fullness of Q-Learning based RL agents in suggesting optimal flight routes and lays the groundwork for future developments in this research domain. The proposed algorithm provides useful information for tourists and business people looking for accurate and affordable flight path forecasts in the Asian region. The various performance metrics such as Reward Accumulation(RA), Episode Length(EL), and Exploration and Exploitation evaluates the proposed model performance and yields an optimal solution.
RECENT SCHOLAR PUBLICATIONS
Soil Health Intelligence System using Multispectral Imaging and Advanced Deep Learning Techniques (SHIDS-ADLT) VS B. Dhanalakshmi, K. Rejini, V Viswanath Shenoi, Arthi A, R. Rajkumar, S ... Communications on Applied Nonlinear Analysis 31 (6), 417 , 2024 2024
Cross-Platform Multimodal Frogeye Leaf Spot Recognition and Classification: Advancing with Cutting-Edge CNN Technologies and Transfer Learning in Diverse Plant Species G Mohan, R Usharani, V Tomar, SK Kuriyal, KP Yuvaraj 2024 7th International Conference on Circuit Power and Computing … , 2024 2024 Citations: 1
Leukemia detection using invariant structural cascade segmentation based on deep vectorized scaling neural network A Arthi, V Vennila, U Arun Kumar Cybernetics and Systems 55 (4), 804-822 , 2024 2024 Citations: 10
Fuzzy-Based Hybrid Approach for Security Impact Evaluation in Healthcare Web Applications JK Chaudhary, A Arthi, S Shalini, C Gunasundari, A Sharma, DN Sahu 2024 International Conference on Advances in Computing, Communication and … , 2024 2024 Citations: 1
A Fuzzy Logic Based (FLB) Hybrid Level of Approach in the Evaluation of Security Impact in Healthcare Type of Web Applications for Secure Informations A Arthi, DN Sahu 2024 1st International Conference on Innovative Sustainable Technologies for … , 2024 2024
Deep convolutional neural networks for early-stage detection and prognostication of lung and colon cancer K Laxmikant, A Arthi, V Vinodhini, B Natarajan, R Bhuvaneswari, ... 2024 International Conference on Integrated Circuits and Communication … , 2024 2024 Citations: 6
A novel q-learning optimization approach for flight path prediction in asian cities KS Reddy, B Natarajan, M Tamilselvi 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-9 , 2023 2023 Citations: 9
An Android-Based Water Quality Monitoring System and Alerting Through SMS SSH S.Prabu, A. Arthi, B.Natarajan, V. Deepak Turkish Online Journal of Qualitative Inquiry 12 (3), 150-170 , 2021 2021
Anti Theft Control of Automatic Teller Machine Using Wireless Sensors R Jaiganesh, L Nagarajan, A Arthi, V Venkatesh Biosc. Biotech. Res. Comm. Special Issue 13 (3), 18-22 , 2020 2020 Citations: 3
Intelligent Transportation System Based On Fingerprint Biometric In Cloud Systems LXNI A Arthi International Journal of Research in Engineering, Science and Management. 1 … , 2018 2018
IOT based low cost smart locker security system L Nagarajan, A Arthi International Journal of Advance Research, Ideas and Innovations in … , 2017 2017 Citations: 15
MOST CITED SCHOLAR PUBLICATIONS
IOT based low cost smart locker security system L Nagarajan, A Arthi International Journal of Advance Research, Ideas and Innovations in … , 2017 2017 Citations: 15
Leukemia detection using invariant structural cascade segmentation based on deep vectorized scaling neural network A Arthi, V Vennila, U Arun Kumar Cybernetics and Systems 55 (4), 804-822 , 2024 2024 Citations: 10
A novel q-learning optimization approach for flight path prediction in asian cities KS Reddy, B Natarajan, M Tamilselvi 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-9 , 2023 2023 Citations: 9
Deep convolutional neural networks for early-stage detection and prognostication of lung and colon cancer K Laxmikant, A Arthi, V Vinodhini, B Natarajan, R Bhuvaneswari, ... 2024 International Conference on Integrated Circuits and Communication … , 2024 2024 Citations: 6
Anti Theft Control of Automatic Teller Machine Using Wireless Sensors R Jaiganesh, L Nagarajan, A Arthi, V Venkatesh Biosc. Biotech. Res. Comm. Special Issue 13 (3), 18-22 , 2020 2020 Citations: 3
Cross-Platform Multimodal Frogeye Leaf Spot Recognition and Classification: Advancing with Cutting-Edge CNN Technologies and Transfer Learning in Diverse Plant Species G Mohan, R Usharani, V Tomar, SK Kuriyal, KP Yuvaraj 2024 7th International Conference on Circuit Power and Computing … , 2024 2024 Citations: 1
Fuzzy-Based Hybrid Approach for Security Impact Evaluation in Healthcare Web Applications JK Chaudhary, A Arthi, S Shalini, C Gunasundari, A Sharma, DN Sahu 2024 International Conference on Advances in Computing, Communication and … , 2024 2024 Citations: 1
Soil Health Intelligence System using Multispectral Imaging and Advanced Deep Learning Techniques (SHIDS-ADLT) VS B. Dhanalakshmi, K. Rejini, V Viswanath Shenoi, Arthi A, R. Rajkumar, S ... Communications on Applied Nonlinear Analysis 31 (6), 417 , 2024 2024
A Fuzzy Logic Based (FLB) Hybrid Level of Approach in the Evaluation of Security Impact in Healthcare Type of Web Applications for Secure Informations A Arthi, DN Sahu 2024 1st International Conference on Innovative Sustainable Technologies for … , 2024 2024
An Android-Based Water Quality Monitoring System and Alerting Through SMS SSH S.Prabu, A. Arthi, B.Natarajan, V. Deepak Turkish Online Journal of Qualitative Inquiry 12 (3), 150-170 , 2021 2021
Intelligent Transportation System Based On Fingerprint Biometric In Cloud Systems LXNI A Arthi International Journal of Research in Engineering, Science and Management. 1 … , 2018 2018