The book presents high quality research papers presented at International Conference on Computational Intelligence (ICCI 2020) held at Indian Institute of Information Technology, Pune, India during 1213 December, 2020. The topics covered are artificial intelligence, neural network, deep learning techniques, fuzzy theory and systems, rough sets, self-organizing maps, machine learning, chaotic systems, multi-agent systems, computational optimization ensemble classifiers, reinforcement learning, decision trees, support vector machines, hybrid learning, statistical learning. metaheuristics algorithms: evolutionary and swarm-based algorithms like genetic algorithms, genetic programming, differential evolution, particle swarm optimization, whale optimization, spider monkey optimization, firefly algorithm, memetic algorithms. And also machine vision, Internet of Things, image processing, image segmentation, data clustering, sentiment analysis, big data, computer networks, signal processing,supply chain management, web and text mining, distributed systems, bioinformatics, embedded systems, expert system, forecasting, pattern recognition, planning and scheduling, time series analysis, human-computer interaction, web mining, natural language processing, multimedia systems, and quantum computing.

Presents research works in the field of computational intelligence Results of ICCI 2020 held in Pune, India during December 2020 Serves as a reference for researchers and practitioners in academia and industry

Autorentext
**Dr. Ritu Tiwari is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Information Technology, Pune, India. Before joining IIIT Pune, She was Associate Professor in Department of Information and Communication Technology at ABV-IIITM Gwalior. She has more than 12 years of teaching and research experience. Her field of research includes Robotics, Artificial Intelligence, Soft Computing and Applications. She has published 05 books and more than 80 research papers in various national and international journals/conferences and is the reviewer for many international journals/conferences. She has received Young Scientist Award from Chhattisgarh Council of Science & Technology in the year 2006. She also received Gold Medal in her post-graduation from NIT, Raipur.
Dr. Apoorva Mishra is an Assistant Professor at the Indian Institute of Information Technology, Pune, India. He has served as the Guest Editor of the SpringerNature Journal 'SN Applied Sciences,' Topical Collection on Engineering: Artificial Intelligence, and has handled 61 manuscripts to final disposition. He has filed two Indian patents and has published around 20 research papers in various peer-reviewed international/national journals and conferences. He is serving as an active reviewer of many renowned SCI-indexed international journals. He has received the 'Gold Medal' from the University for Scoring Highest Marks in M.Tech. In the past, he has also gained industrial experience while working at 'Tata Consultancy Services.'
Dr. Neha Yadav received her Ph.D. in Mathematics from Motilal Nehru National Institute of Technology, (MNNIT) Allahabad, India, in the year 2013. She was post doctorate fellow at Korea University, Seoul, South Korea. She is receiver of Brain Korea (BK-21) Postdoctoral Fellowship given by Government of Republic of Korea. Prior to joining NIT Hamirpur, she taught courses and conductedresearch at BML Munjal University, Gurugram, Korea University Seoul, S. Korea, and The NorthCap University, Gurugram. Her major research area includes numerical solution of boundary value problems, artificial neural networks, and optimization.
**Mario F. Pavone is Associate Professor in Computer Science at the Department of Mathematics and Computer Science of University of Catania, Italy. His research is focused on the design and develops of Metaheuristics applied in several research areas, such as in Combinatorial Optimization; Computational Biology; Network Sciences and Network Social Sciences. He was Visiting Professor in many international University, such as University of Angers in France, University of Nottingham in UK, University of Plymouth in UK, and many others. From 2014 to 2018 he was Chair of the IEEE Task Force on Artificial Immune Systems for the IEEE Computational Intelligence Society, whilst so far he is active member for the followingIEEE Task Forces on: (i) Interdisciplinary Emergent Technologies (as Vice-Chair); (ii) Ethical and Social Implications of Computational Intelligence, and (iii) Artificial Immune Systems (as Vice-Chair from May 1, 2018). He is also member of several Editorial Boards for international journals, as well as member of many Program Committees in international conferences and workshops. He has an extensive experience of organizing successful workshops, symposium, conferences and summer schools. Indeed, he is currently the Chief of the Scientific Directors of the Metaheuristics Summer School (MESS). In his scientific activities, he was also Tutorial and Invited Speakers for several international conferences, and Editor of many special issues in Artificial Life journal, Engineering Applications of Artificial Intelligence, Applied Soft Computing, BMC Immunology, Natural Computing, and Memetic Computing. In May 2018 he was founder of the Advanced New Technologies research laboratory (ANTs Lab), and

Inhalt
Missing Data Imputation for Solar Radiation using Generative Adversarial Networks.- A Survey on Object Detection and Tracking in a Video Sequence.- Story-Plot Recommender using Bidirectional LSTM network.- A Novel Technique for Fake Signature Detection using Two-Tiered Transfer Learning.- Personality Prediction through Handwriting Analysis using Convolutional Neural Networks.- A review on deep learning framework for Alzheimer Disease detection from MRI.- Machine Learning And IoT Based Ultrasonic Humidification Control System For Longevity Of Fruits And Vegetables.- Classification of Melanoma using Efficient Nets with Multiple Ensembles and Metadata.- Performance of Optimization Algorithms in Attention based Deep Learning Model for Fake News Detection System.