This book presents fascinating, state-of-the-art research findings in the field of signal and image processing. It includes conference papers covering a wide range of signal processing applications involving filtering, encoding, classification, segmentation, clustering, feature extraction, denoising, watermarking, object recognition, reconstruction and fractal analysis. It addresses various types of signals, such as image, video, speech, non-speech audio, handwritten text, geometric diagram, ECG and EMG signals; MRI, PET and CT scan images; THz signals; solar wind speed signals (SWS); and…mehr
This book presents fascinating, state-of-the-art research findings in the field of signal and image processing. It includes conference papers covering a wide range of signal processing applications involving filtering, encoding, classification, segmentation, clustering, feature extraction, denoising, watermarking, object recognition, reconstruction and fractal analysis. It addresses various types of signals, such as image, video, speech, non-speech audio, handwritten text, geometric diagram, ECG and EMG signals; MRI, PET and CT scan images; THz signals; solar wind speed signals (SWS); and photoplethysmogram (PPG) signals, and demonstrates how new paradigms of intelligent computing, like quantum computing, can be applied to process and analyze signals precisely and effectively. The book also discusses applications of hybrid methods, algorithms and image filters, which are proving to be better than the individual techniques or algorithms.
Siddhartha Bhattacharyya [LFOSI, FIETE, FIEI, SMIEEE, SMIETI, SMACM, LMCRSI, LMCSI, LMISTE, LMIUPRAI, LMCEGR, MIET (UK), MIRSS, MIAENG, MCSTA, MIAASSE, MIDES, MISSIP, MSDIWC] received his Bachelors in Physics & Optics and Optoelectronics and Masters in Optics and Optoelectronics from the University of Calcutta, India in 1995, 1998 and 2000 respectively, and completed his Ph.D. in Computer Science and Engineering from Jadavpur University, India in 2008. He is currently a Senior Research Scientist at VSB Technical University of Ostrava, Czech Republic, and is also the Principal of the RCC Institute of Information Technology, Kolkata, India. He is co-author of 4 and co-editor of 20 books, and has published over 200 research papers in international journals and conference proceedings. His research interests include soft computing, pattern recognition, multimedia data processing, hybrid intelligence and quantum computing. Sankar K. Pal, a Distinguished Scientist and former Director of Indian Statistical Institute, is currently an INSA Distinguished Professor Chair. He is an alumnus of Calcutta University; the Indian Statistical Institute; and Imperial College, London. He has worked at NASA Johnson Space Center, Houston; the University of California, Berkeley; University of Maryland, College Park; and US-Naval Research Lab, Washington DC. He is an IEEE-CS Distinguished Visitor for the Asia-Pacific region, and has visited 45 countries as a keynote/invited speaker or an academic visitor. He is a fellow of TWAS (The World Academy of Sciences), IEEE, IAPR, IFSA, IRSS, and all four Indian science/engineering academies; He has received various honors, including the highly coveted S.S. Bhatnagar Prize (science award) and Padma Shri (civilian award) in India, and the Khwarizmi International Award in Iran. He is co-author of 20 books, and over 400 publications on pattern recognition, machine intelligence, soft computing, granular mining and big data. He has served on the editorial boards of more than 20 international journals, including IEEE Transactions. Indrajit Pan completed his B.E. in CSE with Honors at The University of Burdwan in 2005, M.Tech. in IT at Bengal Engineering and Science University, Shibpur in 2009, and his Ph.D. (Engineering) from IIEST, Shibpur in 2015. His research interests include social network analysis and cloud computing. Indrajit is now an Associate Professor at the Information Technology Department at RCC Institute of Information Technology, Kolkata. He has published about thirty research papers internationally, as well as a number of edited volumes. Indrajit is a senior member of IEEE, USA and a member of ACM, USA and CSI. Abhijit Das received his B.Tech. in IT from the University of Kalyani in 2003, M.Tech. in IT from the University of Calcutta in 2005 and Ph.D. (Engineering) from the Department of CSE, Jadavpur University in 2016. He has over 15 years of teaching and research experience and has published more than more 30 high-quality papers internationally. He is currently an Associate Professor at the Department of IT, RCC Institute of Information Technology, Kolkata, India, and is guiding 4 research scholars.
Inhaltsangabe
Assessment of UWAC System Performance using FBMC Technique.- Pyramid Based Multi-scale Enhancement Method for Iris Images.- Fuzzy based Classification for Fusion of Palmprint and Iris Biometric Traits.- Employing FPGA Accelerator in Real-time Speaker Identification Systems.- Character Recognition from Handwritten Image using Convolutional Neural Networks.- Malignant Melanoma Classification using Cross Platform Dataset with Deep Learning CNN Architecture.- Simple Exponential Smoothing and its Control Parameter: A Reassessment.- Quantum Inspired BAT Optimization Algorithm for Automatic Clustering of Gray Scale Images.- Face Detection and Expression Recognition using Haar - Cascade Classifier and Fisherface Algorithm.
Assessment of UWAC System Performance using FBMC Technique.- Pyramid Based Multi-scale Enhancement Method for Iris Images.- Fuzzy based Classification for Fusion of Palmprint and Iris Biometric Traits.- Employing FPGA Accelerator in Real-time Speaker Identification Systems.- Character Recognition from Handwritten Image using Convolutional Neural Networks.- Malignant Melanoma Classification using Cross Platform Dataset with Deep Learning CNN Architecture.- Simple Exponential Smoothing and its Control Parameter: A Reassessment.- Quantum Inspired BAT Optimization Algorithm for Automatic Clustering of Gray Scale Images.- Face Detection and Expression Recognition using Haar - Cascade Classifier and Fisherface Algorithm.
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