Artificial Intelligence: Theory and Applications

Proceedings of AITA 2024, Volume 1
Erscheinungsjahr 2025
ISBN: 978-981-961917-7
Verlag: Springer Nature Singapore

Buch, Englisch, 793 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1360 g

Reihe: Lecture Notes in Networks and Systems

This book features a collection of high-quality research papers presented at International Conference on Artificial Intelligence: Theory and Applications (AITA 2024), held during 9–10 August 2024 in Bengaluru, India. The book is divided into two volumes and presents original research and review papers related to artificial intelligence and its applications in various domains including health care, finance, transportation, education, and many more.

Zielgruppe

Research

Autoren/Hrsg.

Sharma, Harish

Kumari, Rajani

Chakravorty, Antorweep

Hussain, Shahid

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

Chapter 1 :Orator-IQ: Interview Preparation and Speech Analyzer.-Chapter 2 :Data Validation using Decomposition Technique for Data Transfer Network.-Chapte 3 :Ransomware Detection using Machine Learning and Explainable AI.-Chapter 4 :Breast Cancer Detection and Classification using ML Techniques.-Chapter 5 :An Optimize Meta-Analysis Secure Data Management in Internet of Medical Things (IoMT) Smart Healthcare Systems .-Chapter 6 :Based on Blockchain and Multi-Access Edge Computing.-Chapte 7 :Smart Farming: Integrating Remote Sensing Data and Machine Learning for Real-Time Crop Monitoring and Decision Support.-Chapter 8 :Silent Listener: Deep Learning-based Visual Speech Recognition.-Chapte 9 :Shadow Traces: An Unraveling Crime using Time Distributed LSTM.-Chapte 10 :A Comprehensive Assessment of Developing a Forecasting Model for Kidney Stone Formation using Deep Learning Approaches.-Chapte 11 :Deep Belief Networks for Unsupervised Feature Learning and Improved Image Recognition.-Chapte 12 :Precision Brain Tumor Segmentation in MRI using SwinFuseNet: A Deep Learning Approach Integrating CNNs, SWIN Transformers, and DCML.-Chapte 13 :Harnessing Open World Machine Learning for Advanced Malware Detection: A SurveyChapte 14 :Hindi Sentiment Analysis on Tweets.-Chapter 15 :Deep Learning For Cervical Cell Analysis: Towards Automatic Diagnosis.-Chapter 16 :AI-Powered Code Editors: Revolutionizing Bug Detection.-Chapter 17 :Machine Learning Strategies for Enhanced Disease Prediction and Management.-Chapter 18 :Q-Learning Embedded Sine Cosine Algorithm for Optimizing Deep CNN in Dengue Disease Spread Detection.-Chapter 19 :Deep Learning in Optimizing Production Inventory Model of Electric Vehicle batteries with Recurrent Quality checks and Electronic Waste Cost Parameters.-Chapter 20 :Challenges and Advancements in Automated Music Transcription: A Focus on Multiple Pitch Estimation.-Chapter 22 :Detecting Parkinson's Disease Early: A Study of Spiral Handwriting Utilizing Pre-Trained CNN Models.-Chapter 23 :How Similar are Programming Solutions Generated by LLM-based Generative AI tools: A Semantic Clone Detection Approach.-Chapter 24:Social Media Harassment Detection Based on Modified Metaheuristic Optimized Adaboost Classification.-Chapter 25ngredient Alcheist: Enhancing Recipe Recommendation Systems through Intelligent Apriori Algorithm.-Chapter 26Deep Learning-Enabled Glaucoma Detection Application: Harnessing Amazon Rekognition for Automated Diagnosis.-Chapter 27Comparative Performance Analysis of Segmentation Methods In Cervigram Images.-Chapter 28ntegrating Explainable AI with Machine Learning for Accurate Liver Disease Diagnosis.-Chapter 29mpowering Knowledge Sharing Through AI-Driven Semantic Video Search.-Chapter 30odelling Real-Time Solar Energy Prediction using an Ensemble Learning Approach.-Chapter 31ssessing Depth of Anesthesia using PPG Signals.-Chapter 32xploring EEG Feature Extraction and Explainable AI for Accurate Depth of Anesthesia Prediction.-Chapter 33oice Control Integrated Navigation System for Autonomous Robots.-Chapter 34valuating The Vietnamese Logistics Companies Using the DEA-Malmquist Model.-Chapter 35ew Approaches for Winner Determination via Minimum Weighted Vertex Cover Computations.-Chapter 36ptimizing Resource Allocation in V2X Networks with Multi-Head Attention based Mechanism using Transformers Networks.-Chapter 37:-HSSN: A Framework to Detect Punjabi Hate Speech in Social Networks.-Chapter 38 DST-DCT Based Adaptive Color Image Watermarking Scheme Using Coati Optimization Algorithm.-Chapter 39cute Lymphoblastic Leukemia Subtypes Detection using Swin Transformer Model.-Chapter 40ccelerating Hate Speech Classification with GPUs: A Multi-Layer Approach with String Matching and Transformers.-Chapter 41:Prioritizing Risks in AI-Enabled EdTech Platforms: An Analytic Hierarchy Process Approach.-Chapter 42Leveraging Pretrained Models for Meat Freshness and Spoilage Detection.-Chapter 43esign and Analysis of a Hybrid Algorithm for Image Steganography and Image Encryption.-Chapter 44: Analysis of Random Vector Functional Link Neural Networks: Approaches and Applications.-Chapter 45:ta Preprocessing and Feature Selection Approach for an Automated Expert Finding System for Academic Events.-Chapter 46andwritten Recognition System using Image Acquisition Technique.-Chapter 47:Eraction of Retinal Blood Vessel using Intensity Histogram.-Chapter 48:omprehensive Analysis of Canine Parvovirus Outbreaks: Predictive Modelling and Evaluation Metrics.-Chapter 49:Use of Artificial Intelligence Over Conventional Methods for Rapid Detection of Alternaria Porri, Responsible for Causing Purple Blotch Disease in Onion Seed.-
Chapter 50:Driven Approaches to Green Building Material Selection using Deep Learning.-Chapter 51:Analysis of Hotel Reviews - A Performance Improvement Model using BERT, VADER& XLNet.-Chapter 52:athfinding in Autonomous Robotics: Balancing Risk, Energy, and Environmental Impact in Diverse Path Networks.-Chapter 53:entification of Hepatocellular Carcinoma Biomarkers using Machine Learning Techniques.-Chapter 54:daptive Cybersecurity for IoT Networks Using Artificial Immune Systems: A Scalable Approach for Real-Time Threat Detection.-Chapter 55:utomated Digital Hand Gesture and Speech Recognition Based Presentations.-Chapter 56:Difficulty Level Prediction on Evaluating the Quality of Question Papers using Bloom's Taxonomy.-Chapter 57 :Advancing Underwater Image Quality Enhancement through Hybrid Deep Learning Architectures
WordAhead: Next Word Prediction Engine.

Über Autor(innen)

Dr.Harish Sharma is an Associate professor at Rajasthan Technical University, Kota in Department of Computer Science & Engineering. He has worked at Vardhaman Mahaveer Open University Kota, and Government Engineering College Jhalawar. He received his B.Tech and M.Tech degree in Computer Engg. from Govt. Engineering College, Kota and Rajasthan Technical University, Kota in 2003 and 2009 respectively. He obtained his Ph.D. from ABV - Indian Institute of Information Technology and Management, Gwalior, India. He is secretary and one of the founder member of Soft Computing Research Society of India. He is a life time member of Cryptology Research Society of India, ISI, Kolkata. He is an Associate Editor of “International Journal of Swarm Intelligence (IJSI)” published by Inderscience. He has also edited special issues of the many reputed journals like “Memetic Computing”, “Journal of Experimental and Theoretical Artificial Intelligence”, “Evolutionary Intelligence” etc. His primary area of interest is nature inspired optimization techniques. He has contributed in more than 105 papers published in various international journals and conferences.

Dr. Antorweep Chakravorty is an Associate Professor at the University of Stavanger. His current research and development work is in the field of applied Blockchains, Big Data, Large Scale Machine Learning, and Data Privacy. He has an interest in real-world problems, especially development of privacy enabled data-driven services in smart energy, healthcare, and smart city domains. Antorweep completed his PhD. in 2015 with a thesis on Privacy Preserving Big Data Analytics at the University of Stavanger, Norway. Along with having a background in applied research in data-driven solutions, he is also involved in mentoring, teaching and supervision.

Dr. Shahid Hussain  is working at University of Canberra as Associate Professor of Biomedical Robotics. Prior to that he has worked as lecturer at University of Wollongong, Australia. Dr. Hussain has obtained his PhD in Mechanical Engineering from the University of Auckland, New Zealand in 2013. His research interests include assistive and rehabilitation robotics, compliant actuation of robots, robot mechanism design and optimization, non-linear dynamics and control of robotic systems, human-robot interaction, biomechanical modelling, engineering education and micro electro-mechanical systems (MEMS). Dr. Hussain has published more than 65 papers in the prestigious journals of the field.

Dr. Rajani Kumari is currently an Assistant Professor at IBS, Bangalore, Off-Campus Centre of ICFAI Foundation for Higher Education (IFHE) University, India. Previously she was an assistant professor at IIIM, Jaipur and St. Xavier's College Jaipur, CHRIST University. She received the PhD degree in computer science in 2015, the MCA and BCA from University of Rajasthan in 2010 and 2006 respectively. She has published more than forty research papers in various international journals/conferences and participated in many national and international conferences and workshops. She edited some special issue in Taylor & Francis and Inderscience journals including Journal of Information and Optimization Sciences (JIOS) and Int. J. of Intelligent Information and Database Systems (IJIIDS). Her research interests include Nature Inspired Algorithms, Swarm Intelligence, Soft Computing, and Computational Intelligence.