This book is a collection of the high-quality research articles in the field of computer vision and robotics which are presented in International Conference on Computer Vision and Robotics (ICCVR 2022), organized by BBD University Lucknow India, during 21 - 22 May 2022. The book discusses applications of computer vision and robotics in the fields like medical science, defence and smart city planning. This book presents recent works from researchers, academicians, industry, and policy makers.
This book is a collection of the high-quality research articles in the field of computer vision and robotics which are presented in International Conference on Computer Vision and Robotics (ICCVR 2022), organized by BBD University Lucknow India, during 21 - 22 May 2022. The book discusses applications of computer vision and robotics in the fields like medical science, defence and smart city planning. This book presents recent works from researchers, academicians, industry, and policy makers.
Prof. Praveen Kumar Shukla is presently working as Professor and Head in the Department of Computer Science and Engineering, Babu Banarasi Das University, Lucknow. He did Ph.D. in Computer Science and Engineering from Dr. A P J Abdul Kalam Technical University, Lucknow. He did B.Tech. in Information Technology and M.Tech. in Computer Science and Engineering. His research area includes fuzzy systems (interval type-2 fuzzy systems and type-2 fuzzy systems), evolutionary algorithms (genetic algorithms), genetic fuzzy systems, multi-objective optimization using evolutionary algorithms, big data analytics, and Internet of things. He has published many papers in national conferences, international conferences, and international journals. He has also published a book "Introduction to Information Security and Cyber Laws" in 2014 with Dreamtech Publishers and published a patent on "Social Media based Framework for Community Moblisation during and post Pandemic" in 2021. He completed one research project on "Particle Swarm Optimization Based Electric Load Forecasting" sponsored by Dr. A P J Abdul Kalam Technical University under TEQIP-III scheme. He is Member of IEEE (Computational Intelligence Society), USA, International Association of Computer Science and Information Technology (IACSIT), Singapore, International Association of Engineers (IAENG), Hong Kong, Society of Digital Information and Wireless Communications (SDIWC), Institutions of Engineers, India, and Soft Computing Research Society (SCRS), India. Dr. Krishna Pratap Singh is Associate Professor at Department of Information Technology, Indian Institute of Information Technology Allahabad. Prior to this, he worked as Assistant Professor (2013-2018) and Lecture (2009-2012) at IIIT Allahabad. He did Ph.D. and Master from IIT Roorkee in 2009 and 2004, respectively. He has published more than 60 research articles in various International Journals and conferences. He isheading Machine Leaning and Optimization Lab at IIITA. His teaching and research interests are machine learning, representation learning, transfer learning, and optimization. Dr. Ashish Kumar Tripathi (Member, IEEE) received his M.Tech. and Ph.D. degrees in Computer Science and Engineering from Delhi Technological University, Delhi, India, in 2013 and 2019, respectively. He is currently working as Assistant Professor with the Department of Computer Science and Engineering, Malviya National Institute of Technology (MNIT), Jaipur, India. His research interests include big data analytics, social media analytics, soft computing, image analysis, and natural language processing. Dr. Tripathi has published several papers in international journals and conferences including IEEE transactions. He is active Reviewer for several journals of repute. Prof. Andries Engelbrecht received the Master's and Ph.D. degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999, respectively. He is currently appointed as Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artificial Intelligence (2007-2018), Head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018).
Inhaltsangabe
Story Telling: Learning to Visualize Sentences Through Generated Scenes.- A Novel Processing of Scalable Web Log Data using Map Reduce Framework.- A Review of Disease Detection of Pre and Post-Harvest Plant Diseases: Recent Developments and Future.- Comparative Study Based on Lung Cancer with Covid-19 Using Deep Learning and Machine Learning.- Low-cost Data Acquisition System for Electric Vehicles.- Machine Learning based Robotic-Assisted Upper Limb Rehabilitation Therapies: A Review.- Performance Analysis of Classic LEACH vs CC-LEACH.- Anomaly Detection in the Course Evaluation Process.- Self Attention Based Efficient U-Net for Crack Segmentation.- Lung Carcinoma Detection from CT Images Using Image Segmentation.- A Deep Learning Based Human Activity Recognition System for Monitoring the Elderly People.- Tweets Classification on the Base of Sentiments using Deep Learning.
Story Telling: Learning to Visualize Sentences Through Generated Scenes.- A Novel Processing of Scalable Web Log Data using Map Reduce Framework.- A Review of Disease Detection of Pre and Post-Harvest Plant Diseases: Recent Developments and Future.- Comparative Study Based on Lung Cancer with Covid-19 Using Deep Learning and Machine Learning.- Low-cost Data Acquisition System for Electric Vehicles.- Machine Learning based Robotic-Assisted Upper Limb Rehabilitation Therapies: A Review.- Performance Analysis of Classic LEACH vs CC-LEACH.- Anomaly Detection in the Course Evaluation Process.- Self Attention Based Efficient U-Net for Crack Segmentation.- Lung Carcinoma Detection from CT Images Using Image Segmentation.- A Deep Learning Based Human Activity Recognition System for Monitoring the Elderly People.- Tweets Classification on the Base of Sentiments using Deep Learning.
Story Telling: Learning to Visualize Sentences Through Generated Scenes.- A Novel Processing of Scalable Web Log Data using Map Reduce Framework.- A Review of Disease Detection of Pre and Post-Harvest Plant Diseases: Recent Developments and Future.- Comparative Study Based on Lung Cancer with Covid-19 Using Deep Learning and Machine Learning.- Low-cost Data Acquisition System for Electric Vehicles.- Machine Learning based Robotic-Assisted Upper Limb Rehabilitation Therapies: A Review.- Performance Analysis of Classic LEACH vs CC-LEACH.- Anomaly Detection in the Course Evaluation Process.- Self Attention Based Efficient U-Net for Crack Segmentation.- Lung Carcinoma Detection from CT Images Using Image Segmentation.- A Deep Learning Based Human Activity Recognition System for Monitoring the Elderly People.- Tweets Classification on the Base of Sentiments using Deep Learning.
Story Telling: Learning to Visualize Sentences Through Generated Scenes.- A Novel Processing of Scalable Web Log Data using Map Reduce Framework.- A Review of Disease Detection of Pre and Post-Harvest Plant Diseases: Recent Developments and Future.- Comparative Study Based on Lung Cancer with Covid-19 Using Deep Learning and Machine Learning.- Low-cost Data Acquisition System for Electric Vehicles.- Machine Learning based Robotic-Assisted Upper Limb Rehabilitation Therapies: A Review.- Performance Analysis of Classic LEACH vs CC-LEACH.- Anomaly Detection in the Course Evaluation Process.- Self Attention Based Efficient U-Net for Crack Segmentation.- Lung Carcinoma Detection from CT Images Using Image Segmentation.- A Deep Learning Based Human Activity Recognition System for Monitoring the Elderly People.- Tweets Classification on the Base of Sentiments using Deep Learning.
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