About the Book
This book explores applied machine learning and deep learning in the field of sensing, vision and sensor-based applications. It includes a series of methodologies, exploration of new applications, presentations on relevant datasets, challenging applications, guidelines, ideas and future scopes. Edited by leading experts in these arenas, the book will be of great interest to academic researchers, graduate students, and industry professionals in the fields of machine learning, deep learning, AI, sensing, computer vision and sensors.
Table of Contents:
Chapter 1 A Tri-modal Fusion Network for Object Detection Using Small Amounts of Low-Quality Data
Yusuke Watanabe, Yuma Yoshimoto and Hakaru Tamukoh
Chapter 2 Arabic Music Classification and Generation using Deep Learning
Mohamed Elshaarawy, Ashrakat Saeed, Mariam Sheta, Abdelrahman Said, Asem Bakr, Omar Bahaa and Walid Gomaa
Chapter 3 An Experimental Study on Speech Emotion Recognition for Bangla Language
Md. Mehedi Hasan, Sarker Tanveer Ahmed Rumee and Moinul Islam Zaber
Chapter 4 Performance Evaluation of Multi-class Bangla Public Sentiment Analysis Using Machine Learning and Embedding Techniques
Md Tazimul Hoque, Syed Tangim Pasha, Rubaiya Khanam, Ashraful Islam, Md Zahangir Alam and Mohammad Nurul Huda
Chapter 5 Cross-Lingual Transfer Learning for Arabic Signature Verification: Dataset and Baseline Evaluation
Tameem Bakr, Ahmed Abdullatif, Kareem Elzeky, Mohamed Elsayed and Rami Zewail
Chapter 6 Empowering Bengali Language in Drone Control with Artificial Neural Networks
Sajjad Hossain Talukder, Noortaz Rezoana, Tanjim Mahmud, Nanziba Basnin, Shourav Chowdhury , Mohammad Shahadat Hossain and Karl Andersson
Chapter 7 Survival Analysis and Therapeutic Drug Targets Identification for Head and Neck Cancer and Chronic Lymphocytic Leukemia Cancer
Md. Anayt Rabbi, Md. Manowarul Islam, Md. Ashraf Uddin, Arnisha Akter, Selina Sharmin
Chapter 8 Intracranial Hemorrhage Segmentation and Application of Interpretable Transfer Learning using Grad-CAM for Classification in Computed Tomography Images
Tazqia Mehrub and Mosabber Uddin Ahmed
Chapter 9 Cervical Cancer Detection Using Multi-Branch Deep Learning Model
Tatsuhiro Baba, Abu Saleh Musa Miah, Jungpil Shin, Md. Al Mehedi Hasan
Chapter 10 An Improved Framework for Classification of Skin Cancer Lesions using Transfer Learning
Tanjim Mahmud, Koushick Barua, Anik Barua, Sudhakar Das, Rishita Chakma, Nanziba Basnin, Nahed Sharmen, Mohammad Shahadat Hossain and Karl Andersson
Chapter 11 An Ensemble Learning Classifier to Predict Net Electricity Generation from Nuclear Power Plants
Mushfiqur Rashid Khan, Faiyaz Fahim, Nahid Hasan, Md. Parveg Plaban
Chapter 12 Deep Learning Optimizers: A Sustainability Perspective on Energy and Emissions
Md Asif Mahmod Tusher Siddique, Md Sakibul Islam, Dr. Ah-Lian Kor, Rashedul Kabir, Nusrath Jahan Happy
Chapter 13 Exploration of Hyperledger Besu in Designing Private Blockchain-based Financial Distribution Systems
Md. Raisul Hasan Shahrukha, Md. Tabassinur Rahmanb and Nafees Mansoorc
Chapter 14 BlockCampus: A Blockchain-Based DApp for Enhancing Student Engagement and Reward Mechanisms in an Academic Community for E-JUST University
Mariam Ayman, Youssef El-harty, Ahmed Rashed, Ahmed Fathy, Ahmed Abdullah, Omar Wassim, Walid Gomaa
Chapter 15 A Crop Recommendation System With a Transformer-Based Deep Learning Model
Md. Nabil Sadd Sammo, Humaira Anzum, Shamim Akhter
About the Author :
Md Atiqur Rahman Ahad, PhD, SMIEEE, SMOPTICA, is an Assoc. Prof. of AI and Machine Learning at University of East London, UK; Visiting Professor of Kyushu Institute of Technology, Japan. He worked as a Professor, University of Dhaka (DU); and a Specially Appointed Associate Professor, Osaka University. He studied at the University of Dhaka, University of New South Wales, and Kyushu Institute of Technology. His authored books are: “IoT-sensor based Activity Recognition”; “Motion History Images for Action Recognition and Understanding”; “Computer Vision and Action Recognition”, in Springer along with several edited books. He published ~200 peer-reviewed papers, ~150 keynote/invited talks, ~50 Awards/Recognitions.
Anton Nijholt is interested in non-traditional human-computer interaction issues. These issues include irrational behavior, deception, food, and humor. They are included in research on entertainment computing, augmented reality, brain-computer interfacing, multimodal interaction, affective interaction, and modelling interactions in smart environments, including human-human interaction, human-robot interaction, human-virtual agent interaction, and playable cities.
He has been program chair or general chair of the main international conferences of affective computing (ACII), entertainment computing (ACE, INTETAIN, ICEC), virtual agents (IVA), faces & gestures (FG), and some others. He organised many workshops on related topics, such as multisensorial augmented reality, humor engineering, human-food interaction, playable cities, and brain-computer interfacing. Recent edited books are "Playable Cities: The City as a Digital Playground", "Making Smart Cities more Playable", and "Brain Art: Brain-Computer Interfaces for Artistic Expression". Nijholt held positions at various universities in Belgium and the Netherlands.
Md Abdus Samad Kamal is working at the Cluster of Electronics and Mechanical Engineering, Graduate School of Science and Technology Gunma University, Japan. His details are in https://www.mst.st.gunma-u.ac.jp/kamal/biog.html
Björn W. Schuller received his diploma, doctoral degree, habilitation, and Adjunct Teaching Professor in Machine Intelligence and Signal Processing all in EE/IT from TUM in Munich/Germany. He is Full Professor of Artificial Intelligence and the Head of GLAM - the
Information Classification: General Group on Language, Audio, & Music - at Imperial College London/UK, Full Professor and Chair of Embedded Intelligence for Health Care and Wellbeing at the University of Augsburg/Germany, co-founding CEO and current CSO of audEERING – an Audio Intelligence company based near Munich and in Berlin/Germany, and permanent Visiting Professor at HIT/China amongst other Professorships and Affiliations. Previous stays include Full Professor at the University of Passau/Germany, Key Researcher at Joanneum Research in Graz/Austria, and the CNRS-LIMSI in Orsay/France. He is a Fellow of the IEEE and Golden Core Awardee of the IEEE Computer Society, Fellow of the BCS, Fellow of the ISCA, Fellow and President- Emeritus of the AAAC, and Senior Member of the ACM. He (co-)authored 1,000+ publications (40k+ citations, h-index=100+), is Field Chief Editor of Frontiers in Digital Health and was Editor in Chief of the IEEE Transactions on Affective Computing amongst manifold further
commitments and service to the community. His 40+ awards include having been honoured as
one of 40 extraordinary scientists under the age of 40 by the WEF in 2015. First-in-the-field of
Affective Computing and Sentiment analysis challenges such as AVEC, ComParE, or MuSe have
been initiated and by now organised overall more than 30 times by him. He is an ERC Starting
and DFG Reinhart-Koselleck Grantee, and consultant of companies such as Barclays, GN,
Huawei, Informatics, or Samsung.
Matthew Turk is the third President of TTIC. He earned a PhD from the Massachusetts Institute
of Technology, an MS from Carnegie Mellon University, and a BS from Virginia Tech.
Prior to joining TTIC in 2019, Turk was a full professor at the University of California, Santa
Barbara, where he continues as Professor Emeritus. His primary appointment was in the
Department of Computer Science, where he served as Department Chair from 2017 to 2019, with
a secondary appointment in Media Arts and Technology, where he served as Chair from 2005 to
2010. He also had affiliate appointments in Electrical and Computer Engineering and the
Dynamical Neuroscience Program and was involved in several interdisciplinary organizations
across campus.
Turk’s primary research interests are in computer vision and machine learning, augmented and
mixed reality, and human-computer interaction. He has received several best paper awards and
has been general or program chair of several major conferences, including CVPR, WACV, ACM
Multimedia, IEEE Face and Gesture Recognition, and International Conference on Multimodal
Interaction (ICMI).
Review :
"This book highlights the cutting-edge research that bridges theoretical advancements with impactful real-world applications. Edited by a highly accomplished team, they have together ensured a well-rounded and visionary exploration of this evolving field. A defining strength of this volume lies in its focus on methodological advancements. Chapters explore cutting-edge techniques, showcasing their practical utility in diverse domains. By applying these advanced methodologies to real-world problems, the book offers readers a clear understanding of both current trends and future opportunities in the field. This volume offers a comprehensive and forward-looking perspective on the integration of machine learning with sensing technologies. It will undoubtedly inspire researchers and practitioners to push the boundaries of what is possible, transforming these innovations into solutions that shape the future."
--Professor Philip H. S. Torr, University of Oxford, UK
