Applied Information Processing Systems

Chapter 1. CNN parameter adjustment for brain tumor classification.- Chapter 2. Advance Fuzzy Radial Basis Function Neural Network.- Chapter 3. Unbounded Fuzzy Radial Basis Function Neural Network Classifier.- Chapter 4. A study on the adaptability of Deep Learning-based Polar coded NOMA in Ultra-Reliable Low-Latency Communication Scenario.- Chapter 5. Heart Rate Variability based Mental Stress Detection using Deep Learning Approach.- Chapter 6. Product Based Market Analysis using Deep Learning.- Chapter 7. Driver drowsiness detection using Deep-Learning Chapter 8. Emotion detection from social media-based using machine learning techniques: A Survey.- Chapter 9. Deep age estimation using sclera images in multiple environment.- Chapter 10. Data Handling Approach for Machine Learning in Wireless Communication: A Survey.- Chapter 11. Breast cancer detection in mammograms using deep learning.- Chapter 12. Deep learning based Parameterized Framework to investigate the influence of Pedagogical Innovations in Engineering Courses.- Chapter 13. Modern Transfer Learning based preliminary diagnosis of COVID-19 using forced cough recordings with Mel-frequency cepstral coefficients.- Chapter 14. Biomedical Text Summarization: A Graph Based Ranking Approach.- Chapter 15. EEG based Diagnosis of Alzheimer's Disease Using  Kolmogorov Complexity.

Dr. Brijesh Iyer received his Ph.D. degree in Electronics and Telecommunication Engineering from Indian Institute of Technology, Roorkee, India, in 2015. He is Associate Professor in the University Department of E&TC Engineering at Dr. Babasaheb Ambedkar Technological University, Lonere (A State Technological University). He is a recipient of INAE research fellowship in the field of Engineering. He had 02 patents to his credit and authored over 50 research publications in peer-reviewed reputed journals and conference proceedings. He had authored 05 five books on curricula as well as cutting-edge technologies like sensors and healthcare technology. He has served as Program Committee Member of various international conferences and Reviewer for various international journals. His research interests include RF front-end design for 5G and beyond, IoT and biomedical image/signal processing.

 

Dr. Debashis Ghosh is presently working as Full Professor and Head of the Department of E&CE Engineering at IIT Roorkee. He had earned his B.E., M.Sc.(Engineering) and Ph.D. from MNIT, Jaipur, IISC Bangalore in the year 1993, 1996 and 2000, respectively, in the area of E&CE Engineering as a major. He was working as Visiting Professor to the many reputed overseas Technological Institutes/Universities. He is a recipient of "Excellence in Teaching" award of Multimedia University, Malaysia, in the year 2007. He has a vast experience of handling research and consultancy projects at IIT Guwahati and IIT Roorkee to his credit. He had published several research papers in various journals and conferences of international and national repute. His area of interest includes communication systems & signal processing, cognitive radio & sensor networks, image & video processing, computer vision & pattern