International Conference on Innovative Computing and Communications

Chapter 1. Explanation Based Serendipitous Recommender System (EBSRS).- Chapter 2. Introduction of feature selection and leading-edge technologies viz. TENSORFLOW, PYTORCH and KERAS: An empirical study to improve prediction accuracy of cardiovascular disease.- Chapter 3. Campus Placement Prediction System using Deep Neural Networks.- Chapter 4. Intensity of Traffic Due to Road Accidents in USA: A Predictive Model.- Chapter 5. Credit Card Fraud Detection using Blockchain and Simulated Annealing k-means Algorithm.- Chapter 6. Improving Accuracy of Deep Learning Based Compression Techniques by Introducing Perceptual Loss in Industrial IoT.- Chapter 7. Characterization and Prediction of Various Issue Types: A Case Study on the Apache Lucene System.- Chapter 8. Heart Disease prediction using Machine Learning Techniques: A Quantitative Review.- Chapter 9. Enhancing CNN with Pre-processing Stage in Illumination Invariant Automatic Expression Recognition.- Chapter 10. An Expert Eye for Identifying Shoplifters in Mega Stores.- Chapter 11. Sanskrit Stemmer Design : A Literature Perspective.- Chapter 12. Predicting Prior Academic Failure of Students' using Machine Learning Approach.- Chapter 13. Deep Classifier for News Text Classification using Topic Modelling Approach.- Chapter 14. Forecasting covid-19 cases using Deep CNN LSTM model.- Chapter 15. Multi-resolution video steganography technique based on Stationary wavelet transform (SWT) and Singular value decomposition (SVD).- Chapter 16. A novel Dual Threshold Weighted Feature Detection for Spectrum Sensing in 5G systems.- Chapter 17. A Systematic Review On Various Attack Detection Methods For Wireless Sensor Networks .- Chapter 18. Electronic Beam Steering in Timed Antenna Array by Controlling the Harmonic Patterns with Optimally Derived Pulse-Shifted Switching Sequence.- Chapter 19. Classification of attacks on MQTT based IoT system using Machine learning techniques.- Chapter 20. Encrypted Traffic Classification

Dr. Ashish Khanna has 16 years of expertise in Teaching, Entrepreneurship, and Research & Development. He received his Ph.D. degree from National Institute of Technology, Kurukshetra. He has completed his M. Tech. and B. Tech. from GGSIPU, Delhi. He has completed his Post-Doc from Internet of Things Laboratory at Inatel, Brazil, and University of Valladolid, Spain. He has published around 55 SCI indexed papers in IEEE Transaction, Springer, Elsevier, Wiley, and many more reputed Journals with cumulative impact factor of above 100. He has around 120 research articles in top SCI/ Scopus journals, conferences and book chapters. He is Co-Author of around 30 edited and text books. His research interest includes distributed systems, MANET, FANET, VANET, IoT, machine learning, and many more. He is Originator of Bhavya Publications and Universal Innovator Laboratory. Universal Innovator is actively involved in research, innovation, conferences, startup funding events,and workshops. He has served the research field as a Keynote Speaker/ Faculty Resource Person/ Session Chair/ Reviewer/ TPC Member / post-doctorate supervision. He is Convener and Organizer of ICICC conference series. He is currently working at the Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology, under GGSIPU, Delhi, India. He is also serving as Series Editor in Elsevier and De Gruyter publishing houses.

Dr. Deepak Gupta received a B.Tech. degree in 2006 from the Guru Gobind Singh Indraprastha University, India. He received M.E. degree in 2010 from Delhi Technological University, India and Ph.D. degree in 2017 from Dr. APJ Abdul Kalam Technical University, India. He has completed his Post-Doc from Inatel, Brazil. With 13 years of rich expertise in teaching and two years in the industry; he focuses on rational and practical learning. He has contributed massive literature in the fields of Intelligent Data Analysis, Biomedical