Dr P.Chandana

Verified email at gmail.com

Coomputer Science and Engineering
Institute of Aeronautical Engineering



                                         

https://researchid.co/drchandana

Dr. P.Chandana is currently working as an Associate Professor in CSE. She received Doctorate in Computer Science and Engineering from Andhra University for the research work on “Sketch Based Image Retrieval For Efficient Identification of Art Forensics”; MCA from IGNOU; M.Tech in Computer Science and Technology from Andhra University, Visakhapatnam; B.Sc in Maths, Electronics and Computers from Andhra University; She served in academics more than 12 years in various Engineering Colleges: VITS, Miracle Engineering College(Visakhapatnam), VIIT(Visakhapatnam), Raghu Engineering College (Visakhapatnam). Her research interests are Image Processing, Computer Vision, Internet of Things, Data Mining, Information Retrieval, Machine Learning, Artificial Intelligence, Natural Language Processing, Semantic Web, Wireless Networks. She has published 12 papers in international journals a book on “A Comprehensive Survey of Geographical Routing and its Impact on Mobility Models in Multi-hop Wireless

EDUCATION

Ph.D in Computer Science and Engineering, M.Tech in Computer Science and Technology, MCA from IGNOU

RESEARCH INTERESTS

Data Mining, Machine Learning, Data Analytics, Natural Language Processing, Image Proccessing, Computer Vision, Social Media Mining

FUTURE PROJECTS

Voice to Text Recognition for smart desktop applications

This project is intended to help out the blind persons and software employees to use resources of a computer efficiently with a desktop assistant gets activated with a voice.


Applications Invited
Collaborators and Students

Need and Resource management during Natural Calamities

This project is to provide the immediate help for the people who got stucked at the time of Natural calamities like Flood, EarthQuakes, Tornados etc. The aim of this project is to use Google Maps, Social Media to have a communication and tacking of nearby resource centers or ngos for extending the help.


Applications Invited
Collaborators and Students
6

Scopus Publications

82

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • An effective identification of crop diseases using faster region based convolutional neural network and expert systems
    P. Chandana, G. S. Pradeep Ghantasala, J. Rethna Virgil Jeny, Kaushik Sekaran, Deepika N., Yunyoung Nam, and Seifedine Kadry

    International Journal of Electrical and Computer Engineering, ISSN: 20888708, Pages: 6531-6540, Published: December 2020 Institute of Advanced Engineering and Science
    The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.

  • Implementation of face and eye detection on DM6437 board using simulink model
    B. Vijayalaxmi, Kaushik Sekaran, N. Neelima, P. Chandana, Maytham N. Meqdad, and Seifedine Kadry

    Bulletin of Electrical Engineering and Informatics, ISSN: 20893191, eISSN: 23029285, Pages: 785-791, Published: April 2020 Institute of Advanced Engineering and Science
    Driver Assistance system is significant in drriver drowsiness to avoid on road accidents.  The aim of this research work is to detect the position of driver’s eye for fatigue estimation. It is not unusual to see vehicles moving around even during the nights. In such circumstances there will be very high probability that a driver gets drowsy which may lead to fatal accidents. Providing a solution to this problem has become a motivating factor for this research, which aims at detecting driver fatigue. This research concentrates on locating the eye region failing which a warning signal is generated so as to alert the driver. In this paper, an efficient algorithm is proposed for detecting the location of an eye, which forms an invaluable insight for driver fatigue detection after the face detection stage. After detecting the eyes, eye tracking for input videos has to be achieved so that the blink rate of eyes can be determined.

  • Deep learning convolutional neural network (CNN) With Gaussian mixture model for predicting pancreatic cancer
    Kaushik Sekaran, P. Chandana, N. Murali Krishna, and Seifedine Kadry

    Multimedia Tools and Applications, ISSN: 13807501, eISSN: 15737721, Issue: 15-16, Pages: 10233-10247, Published: 1 April 2020 Springer Science and Business Media LLC
    The tremendous research towards medical health systems are giving ample scope for the computing systems to emerge with the latest innovations. These innovations are leading to the efficient implementations of the medical systems which involve in automatic diagnosis of the health related problems. The most important health research is going on towards cancer prediction, which has different forms and can be affected on different portions of the body parts. One of the most affected cancer that predicted to be incurable are Pancreatic Cancer, which cannot be treated efficiently once identified, in most of the cases it found to be unpredictable as it lies in the abdomen region below the stomach. Therefore the advancements in the medical research is trending towards the implementations of an automated systems which identifies the stages of cancer if affected and provide the better diagnosis and treatment if identified. Deep learning is one such area which extended its research towards medical imaging, which automates the process of diagnosing the problems of the patients when appended with the set of machines like CT/PET Scan systems. In this paper, the deep learning strategy named Convolutional Neural network (CNN) model is used to predict the cancer images of the pancreas, which is embedded with the model of Gaussian Mixture model with EM algorithm to predict the essential features from the CT Scan and predicts the percentage of cancer spread in the pancreas with the threshold parameters taken as a markers. The experimentation is carried out on the CT Scan images dataset of pancreas collected from the Cancer Imaging Archive (TCIA) consists of approximately 19,000 images supported by the National Institutes of Health Clinical Center to analyze the performance of the model.

  • Design of optimal search engine using text summarization through artificial intelligence techniques
    Kaushik Sekaran, P. Chandana, J. Rethna Virgil Jeny, Maytham N. Meqdad, and Seifedine Kadry

    Telkomnika (Telecommunication Computing Electronics and Control), ISSN: 16936930, eISSN: 23029293, Pages: 1268-1274, Published: 2020 Universitas Ahmad Dahlan
    Natural language processing is the trending topic in the latest research areas, which allows the developers to create the human-computer interactions to come into existence. The natural language processing is an integration of artificial intelligence, computer science and computer linguistics. The research towards natural Language Processing is focused on creating innovations towards creating the devices or machines which operates basing on the single command of a human. It allows various Bot creations to innovate the instructions from the mobile devices to control the physical devices by allowing the speech-tagging. In our paper, we design a search engine which not only displays the data according to user query but also performs the detailed display of the content or topic user is interested for using the summarization concept. We find the designed search engine is having optimal response time for the user queries by analyzing with number of transactions as inputs. Also, the result findings in the performance analysis show that the text summarization method has been an efficient way for improving the response time in the search engine optimizations.

  • An Efficient Mixture Model Approach in Brain-Machine Interface Systems for Extracting the Psychological Status of Mentally Impaired Persons Using EEG Signals
    N. Murali Krishna, Kaushik Sekaran, Annepu Venkata Naga Vamsi, G. S. Pradeep Ghantasala, P. Chandana, Seifedine Kadry, Tomas Blazauskas, and Robertas Damasevicius

    IEEE Access, eISSN: 21693536, Pages: 77905-77914, Published: 2019 Institute of Electrical and Electronics Engineers (IEEE)
    We propose an efficient mixture classification technique, which uses electroencephalography (EEG) signals for establishing a communication channel for the physically challenged or immobilized people, by the usage of the brain signals. In order to identify the emotion expressions by an immobilized person, we introduce a novel approach for emotion recognition based on the generalized mixture distribution model. The main benefit of utilizing this model is that it is an asymmetric distribution, which helps to extract the EEG signals, which are either in symmetric or asymmetric form. The skew Gaussian distribution helps to identify the small duration EEG signal sample and helps toward better recognition of emotions in both clean and noisy EEG signals. The proposed method is particularly well suited for the high variability of the EEG signal allowing the emotions to be identified appropriately. The features of the brain signals are extracted by using cepstral coefficients. The extracted features are classified into different emotions using mixture classification techniques. In order to validate the model, six mentally impaired subjects are considered in the age group of 60–68, and an 8-channel EEG signal is utilized to collect the EEG signals under audio-visual stimuli. The basic emotions considered in this study include happy, sad, neutral, and boredom and an average emotion recognition accuracy of 89% is achieved.

  • Comparing the Access Control Mechanism in Database, Cloud and Femtocells
    Harshita R. Jhurani, Pindi Chandana, Yarram Vijay Kumar Reddy, and Mangipudi Sharada

    Proceedings of the 2nd International Conference on Electronics, Communication and Aerospace Technology, ICECA 2018, Pages: 20-25, Published: 26 September 2018 IEEE
    Security has been a major issue since the evolution of mankind. Access control refers to providing access to data only to specified users. In the present time, various mechanisms are used and many policies have been implemented to secure the confidential data. These mechanisms are not always easy to be implemented. Many challenges are met during the execution and various devices have been designed in an ad-hoc fashion to meet the present day requirements. The deployment of these devices and methods in various fields has solved the protection issue to a large extent. This paper represents the SQLIA and XSS attacks, the techniques that are compared to few mechanisms used to restrict unethical access to database, cloud and femtocells that followed in day-to-day life, and the challenges met to obtain them.

RECENT SCHOLAR PUBLICATIONS

  • An effective identification of crop diseases using faster region based convolutional neural network and expert systems
    P Chandana, GP Ghantasala, JRV Jeny, K Sekaran, N Deepika, Y Nam, ...
    International Journal of Electrical and Computer Engineering (IJECE) 10 (6 2020

  • An Effective Identification of Crop diseases using Faster Region based Convolutional Neural Network and Expert Systems
    DN Seifedine Kadry P. Chandana , G. S. Pradeep Ghantasala , J. Rethna Virgil ...
    International Journal of Electrical and Computer Engineering (IJECE) - http 2020

  • Design of optimal search engine using text summarization through artificial intelligence techniques
    K Sekaran, P Chandana, JRV Jeny, MN Meqdad, S Kadry
    Telkomnika 18 (3), 1268-1274 2020

  • Implementation of face and eye detection on DM6437 board using simulink model
    B Vijayalaxmi, K Sekaran, N Neelima, P Chandana, MN Meqdad, S Kadry
    Bulletin of Electrical Engineering and Informatics 9 (2), 785-791 2020

  • An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG signals
    NM Krishna, K Sekaran, AVN Vamsi, GSP Ghantasala, P Chandana, ...
    IEEE Access 7, 77905-77914 2019

  • Deep learning convolutional neural network (CNN) With Gaussian mixture model for predicting pancreatic cancer
    KSPCNMKS Kadry
    Multimedia Tools and Applications, pp 1–15 2019

  • Object Identification Using Image Fusion
    DYS P. Chandana, Dr. P. Srinivasa Rao
    International Journal of Advance Research, Ideas and Innovations in 2017

  • An efficient content-based image retrieval (CBIR) using GLCM for feature extraction
    P Chandana, PS Rao, CH Satyanarayana, Y Srinivas, AG Latha
    Recent Developments in Intelligent Computing, Communication and Devices, 21-30 2017

  • Sketch Retrieval using Contour Detection by Chain Codes
    PC Mohan Mahanty , D. Kiranmayi
    International Journal of Advanced Research in Computer and Communication 2015

  • Comparison between Local Binary Pattern and Chain Code Techniques for Image Retrieval using Sketches
    DYS P. Chandana ,prof. P. Srinivas Rao
    International Journal of Advanced Research in Computer and Communication 2015

  • IMPLEMENTING GAUSSIAN MIXTURE MODEL FOR IDENTIFYING IMAGE SEGMENTATION
    S Eddula, P Chandana, BS Swaroop
    2012

  • A novel approach for unrestricted watermarking method using wavelet transform
    R Nageswararao, P Chandana, M Madhavi, I Visakhapatnam, I Ongole
    Int. J. Sci. Adv. Technol 1, 255-261 2011

  • A Novel approach for Unrestricted Watermarking method using Wavelet Transform
    RNPCM Madhavi
    2011

  • Dynamic Bandwidth Allocation in WIMAX
    JP P.Chandana,A.Gauthami Latha
    ICSCI 2010

  • Adaptive Based Offline Handwriting Recognition using Neural Network
    P Chandana
    IJSCT 2010

  • & Damaševičius, R.(2019). An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG
    NM Krishna, K Sekaran, AVN Vamsi, GP Ghantasala, P Chandana, ...
    IEEE Access 7, 77905-77914

MOST CITED SCHOLAR PUBLICATIONS

  • Deep learning convolutional neural network (CNN) With Gaussian mixture model for predicting pancreatic cancer
    KSPCNMKS Kadry
    Multimedia Tools and Applications, pp 1–15 2019
    Citations: 31

  • An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG signals
    NM Krishna, K Sekaran, AVN Vamsi, GSP Ghantasala, P Chandana, ...
    IEEE Access 7, 77905-77914 2019
    Citations: 16

  • Design of optimal search engine using text summarization through artificial intelligence techniques
    K Sekaran, P Chandana, JRV Jeny, MN Meqdad, S Kadry
    Telkomnika 18 (3), 1268-1274 2020
    Citations: 10

  • & Damaševičius, R.(2019). An efficient mixture model approach in brain-machine interface systems for extracting the psychological status of mentally impaired persons using EEG
    NM Krishna, K Sekaran, AVN Vamsi, GP Ghantasala, P Chandana, ...
    IEEE Access 7, 77905-77914
    Citations: 6

  • Implementation of face and eye detection on DM6437 board using simulink model
    B Vijayalaxmi, K Sekaran, N Neelima, P Chandana, MN Meqdad, S Kadry
    Bulletin of Electrical Engineering and Informatics 9 (2), 785-791 2020
    Citations: 5

  • An efficient content-based image retrieval (CBIR) using GLCM for feature extraction
    P Chandana, PS Rao, CH Satyanarayana, Y Srinivas, AG Latha
    Recent Developments in Intelligent Computing, Communication and Devices, 21-30 2017
    Citations: 5

  • An effective identification of crop diseases using faster region based convolutional neural network and expert systems
    P Chandana, GP Ghantasala, JRV Jeny, K Sekaran, N Deepika, Y Nam, ...
    International Journal of Electrical and Computer Engineering (IJECE) 10 (6 2020
    Citations: 4

  • Sketch Retrieval using Contour Detection by Chain Codes
    PC Mohan Mahanty , D. Kiranmayi
    International Journal of Advanced Research in Computer and Communication 2015
    Citations: 3

  • Comparison between Local Binary Pattern and Chain Code Techniques for Image Retrieval using Sketches
    DYS P. Chandana ,prof. P. Srinivas Rao
    International Journal of Advanced Research in Computer and Communication 2015
    Citations: 1

  • A novel approach for unrestricted watermarking method using wavelet transform
    R Nageswararao, P Chandana, M Madhavi, I Visakhapatnam, I Ongole
    Int. J. Sci. Adv. Technol 1, 255-261 2011
    Citations: 1