Algorithms in Advanced Artificial Intelligence: Taylor and Francis Proceedings in Computer Science and Engineering
Editat de R.N.V. Jagan Mohan, B.H.V.S. Rama Krishnam Raju, G.N.V. Sirishaen Limba Engleză Paperback – 23 noi 2026
The book covers topics like Machine learning, Deep learning, Explainable AI, Quantum AI, and more, facilitating interdisciplinary collaboration through various formats including keynote addresses, workshops, and panel discussions. It aims to provide networking opportunities while showcasing innovations in AI from fields like healthcare, Agriculture, and other technology.
It is useful for students, researchers, industry practitioners and experts working in the field of Artificial Intelligence, machine learning and intelligent computing.
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Specificații
ISBN-13: 9781041457084
ISBN-10: 1041457081
Pagini: 754
Dimensiuni: 210 x 280 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Taylor and Francis Proceedings in Computer Science and Engineering
ISBN-10: 1041457081
Pagini: 754
Dimensiuni: 210 x 280 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Taylor and Francis Proceedings in Computer Science and Engineering
Public țintă
Academic and Undergraduate CoreCuprins
Gold Price Prediction Using LS-SVM, LSTM, and ANN: A Machine Learning Approach. Privacy-Preserving Federated Learning for Intrusion Detection in IoT and IoV: A Comparison of Differential Privacy, Homomorphic Encryption, and Mimic Learning. Quantum-Enhanced Deep Learning for Brain Tumor Classification. A Comprehensive Survey of Machine Learning Solutions for Malware Detection in Android Devices. Adaptive Deep Learning Method for Age-Related Disease Identification. A Comparative Model to Integrate Instruction-Driven Computing Systems with Models of Human Behaviour: Design, Implementation and Evaluation of Comparative Study Between Systems (CSBS). Increase the Sustainability and Productivity of Prawn Farming Using Convolutional Neural Network (CNN). Alzheimer's Detection Through Linguistic Features In Narrative Speech Using Deep Neural Networks. AI Powered Study Tutor Using PDF Textbooks and Local Generative AI. Wichain: Rust-Powered Blockchain for Localized Secure Messaging. Advanced Ensemble Learning Framework for Accurate Startup Valuation, Investment Forecasting, And Strategic Investor Decision-Making. Crop Price Forecasting in Indian Agricultural Markets Using Optimized Machine Learning. AI-Driven Risk Prediction Model (AI-RPM) for Rock-Fall Hazards. Automated Detection of Stuttering and Therapeutic Recommendations Utilizing Machine Learning. Explainable and Multimodal DL for Parkinsons Disease Diagnosis and Their Models Modalities and Clinical Integration: A Review. Deep Reinforcement Learning for Privacy-Aware and Scalable Scheduling in Distributed Healthcare Systems for Cloud Computing. Enhanced Ransomware Detection Using VMware-Based Feature Extraction and Modified CNN 2D Optimization. Improved IoT Anomaly Detection with Privacy Preserving VAE with MHEF and DETDO Optimization. PiTLiD: A Convolutional Neural Network for Apple Plant Disease Detection. Fingertrust - A Framework for Cloud Fingerprint Authentication Scheme. Predicting FSO Received Power with Environmental Data and ML Techniques. Speech Processing Approaches for Dysarthria Detection and Assessment: A Deep Learning-Based Framework. A Hybrid Approach to Secure Data Transmission. Quantum-Graph Causal Networks: Hybrid Quantum-Inspired Graph Neural Models for Causal Discovery in High-Dimensional Healthcare Data. Recent Trends and Challenges in Automated Detection and Staging of Lung Cancer Using Deep Learning. A Dual-Purpose AI Framework for Scalable Tableau Education: Automating Instruction and Assessment. Brain Age Prediction Using Deep Learning Approaches. Enhancing Lung Cancer Diagnosis Testing Through a Hybrid Approach. Fake News Detection in the Digital Age: A Robust and Interpretable AI-Based System. Agentic AI Driven Intrusion Detection Using Game Theoretic Hybrid SVM and Autoencoder Framework for Known and Unknown Attacks. CNN Architectures for Robust Image Classification. Federated And Privacy-Aware Intelligence for Asthma Risk Prediction Techniques Challenges and Future Directions. Towards Trustworthy and Accountable AI Systems: Synthesizing ESG Integration, Stakeholder Engagement and Lifecycle Governance. Automated Detection and Severity Grading of Knee Osteoarthritis Using Transfer Learning. Ensemble Deep Learning Framework for Early Diagnosis of Eye Disorders. Novelty on Kidney Based CT Images Using Transfer Learning Finetuning Techniques and Explainable AI and Generative AI. Smart Nutrient-Infused Drip Irrigation System for Tray-Based Brinjal Cultivation Using Random Forest Modeling. Analyze and Predict the Use of Digital Twins and Heuristic Models on Real-Time Patient Data. TwinSecure: Digital Twin for Smart Building Entry Using Biometric Liveness. Adaptive Night–Time Object Detection for Road Safety Using Vision Transformers. GNN-Based Approximation of Node Centralities in Homogeneous Graphs. A Comprehensive Review of AI based Missed Polyp Risk Prediction in Colonoscopy. Multi-Modal AVSC with Human Presence Verification. Touchless PowerPoint Slide Navigation System using Hand Gestures and Voice-based Status. AI-Driven Scene Recognition for Safe Drone Landings. Enhancing Log File Analysis with Template Mining Techniques. A Framework for Reconstructing Standard Electrocardiogram Leads from a Reduced Set of Inputs for Efficient Cardiac Monitoring. Cardiovascular Post-Acute Sequelae of SARS-CoV-2 (PASC): A Systematic Review of Mechanisms, Evidence Gaps, and a Predictive Framework for Future Research. Deep Learning-based Identification of Hemorrhagic Stroke in Brain Using Healthcare Imagery Data. Predicting Adverse Drug Reaction Side Effects via Drug-Drug Interactions Using Machine Learning. ShreshtaHire: AI Enabled Mock Interview and Candidate Evaluation System. Pose Orientation based Face Recognition Using Discrete Cosine Transform and Quantum Computing. Secure Online Voting with Blockchain and Face Recognition Authentication. AgroScan: A Deep Learning Approach for Multi-Class Leaf Disease Diagnosis. Decentralized Identity and Secure Data Exchange System For E-Governance. FundChain: A Decentralized Crowdfunding Platform Using Ethereum Smart Contracts. Multimodal AI Tutor for Smarter Educational Content Access. Social Media Image Captioning Using CNN and Transformer Models. Clustering and Anomaly Detection of Power Quality Disturbances Using Unsupervised Machine Learning. Silent Lip Reading Approach for Personal Authentication and Security. Phyx- Real-time AI Physiotherapist in 3D using a Monocular Camera. A Conversational AI System for Campus Queries: Development and Evaluation of a College Chatbot. Federated Learning for 6G Networks: Privacy-Preserving Beamforming Optimization. Smart GradeX-An Automated Exam Paper Evaluation. Scalable Feature Selection using ReliefF aided by Mutual Information for High Dimensional Micro Array Data. Driving Decision Strategy (DDS) Based on Machine Learning for Autonomous Vehicle. Smart Energy Prediction for Electric Buses Using Machine and Deep Learning. Smart Medicine Dispenser for Elderly with AI-Based Tablet Verification. Deep Unmixing-Classifier for Gas Detection using Hyperspectral Images via a 3D-CNN Autoencoder. Detection of Monkeypox from Skin Lesion Images Using Deep Learning Networks and Explainable Artificial Intelligence. AI-Driven Platform for Fashion Design and Virtual TryOn. Detection of Fault in Railway Track Using Image Processing and Fuzzy Logic. Parameter-Based Classifier for ADHD and Autism with Unique and Overlapping Trait Identification. Voice-Driven Exam Support System for Visually Impaired Students. Marine Environmental Monitoring Via Attention Enhanced Yolov10 for Debris Detection. Hybrid Swarm Intelligence-Based Feature Selection with ResNet50 and XGBoost for Potato Disease Classification. A Deep Learning-Powered Virtual Interview Assistant Using Voice Transcription and Sentiment Analysis. ML–Driven Dermatology Assistant and Recommender. AI-Powered Behavioural Surveillance in Educational and Residential Settings Using Pose Detection and Audio Analysis. Optimizing Data Efficiency In News Topic Classification Using Deep Learning. QML-Based Decomposition and Optimization of Vehicle Routing Problems under Real-World Constraints. Bridge Mentor: An AI-Driven Integrated Platform for Academic and Career Guidance. Smart College Recommendation System for JEE Students. Evaluation of Predictive Models and Framework for Forecast Verification in West Godavari District, Andhra Pradesh: A NASA POWER Pilot Study. Real-Time DoS Attack Detection via Machine Learning. Intelligent Web Scraping using Natural Language Processing and Streamlit for Automated Information Extraction. Invisible Bias, Visible Impact: Ethical Pathways to Trust in AI-Driven Keyword Research in Search Engine Marketing. The Consensus Paradox in Automated AI Peer Review. ResNet-Enhanced HealthFed: A Blockchain-Based Federated Learning Framework with Adaptive Privacy and Scalability for Healthcare Applications. Hybrid Modeling Approach for Profit Optimization in Agricultural Supply Chains. AI-Powered Crop Health Monitoring and Agricultural Equipment Sharing System. Scalable and Efficient Model Compression through Knowledge Distillation. Early Osteoporosis Prediction Using a Hybrid Deep Learning Method. Detecting Ovarian Cancer Early using a State-of-the-Art Machine Learning Approach. Hybrid and Chaotic Optimization of Cloud-IoT Task Scheduling: The Insights of Performance, Scalability, and Energy Efficiency. Alzheimer's Disease Progress May Be Slowed by Early Diagnosis and Therapy. Multi-Stage Machine Learning Model Screening for Autism Spectrum Disorder in All Age Groups. Real-Time Bitcoin Price Prediction through Streaming Data and Machine Learning. Using Genetic Algorithms to Forecast Air Quality Indexes with an Enhanced Extreme Learning Machines. ForenSiX: AI-Powered Six-Module Toolkit for Incident Forensics. Personalised Learning Path Generation with Adaptive Skill Trees. Exponentiated Inverse Half Logistic Distribution: A Software Reliability Growth Model. Exponentiated Inverse Half Logistic Distribution: Two Step Estimation. A Secure Image Encryption Algorithm Based on the Rubik's Cube Principle. Smart Retail Analytics Using AI-Powered CCTV Surveillance. SecureMed: A Blockchain-Integrated Biometric Authentication Framework for Electronic Health Record Management. Time Series Traffic Prediction with Vehicle-Type Suggestions. AI-Powered Hybrid Machine Learning Model for Disease Prediction and Personalized Health Recommendations. Indic-VQA: A Multimodal Framework for Visual Question Answering and Multilingual Translation. Medicinal Plant Leaf Detection Using Machine Learning with Maximum Multilayer Perceptron. Enhancing and Ensuring Regulatory Compliances Using Blockchain Technology in Electronic Health Records. A Hybrid Machine Learning Framework for Wafer Defect Detection and Equipment Health Prediction in Semiconductor Manufacturing. Optimizing Sleep Disorder Diagnosis with a Stacking Classifier. Clustering based Trust Aware Big Data Task Scheduling in Cloud Computing using Binary Osprey Optimization. Ethical CV: Deep-fake Detection Via Biological Signals. Heart Disease Prediction with Quantum Support Vector Machines Versus Traditional Machine Learning Approaches.
Notă biografică
R.N.V. Jagan Mohan is a Professor in the Computer Science and Engineering Department at Sagi Rama Krishnam Raju Engineering College, Bhimavaram. He obtained his Ph.D. from Acharya Nagarjuna University in 2015 under Dr. Kurra Raja Sekhara Rao and holds an M.Tech from Jawaharlal Nehru Technological University, completed in 2010. He has published about 100 papers, secured 6 patents (1 internationally), and authored 9 books (2 internationally). Co-supervisors Dr. Bokka Yugandhar and Dr. K. Dileep Kumar Kadali. Also, Supervised Ph.D. Two candidates at J.N.T.U. Kakinada since 2022. He participated in a joint research project on autism trajectories in electronic health records in collaboration with Israel, funded by the Govt of India. Organized ANRF Sponsored 3rd International Conference on Algorithms in Advanced Artificial Intelligence, Organized dates at 11nd-13th December 2025, Dept of CSE, SRKR Engineering College, Bhimavaram-534204.DST-SERB Sponsored International Conference on Algorithms in Advanced Artificial Intelligence, Organized dates at 22nd-24th December 2023, Dept of CSE, SRKR Engineering College, Bhimavaram-534204. AICTE Sponsored National Conference on Productivity, Quality, Reliability, Optimization and Computational Modeling, Organized dates at 18th – 20th December 2019, Dept of CSE & IT, SRKR Engineering College, Bhimavaram-534204. Three Faculty programs organized Webinar on Blockchain Technology: Insights and Applications,13th August, 2022 at Dept of CSE, SRKR Engineering College, Bhimavaram. Resource Person by Dr. Hussein El Ghor, Professor in CSE, Lebanese University, Lebanon. Faculty Development Program on Data Science and Its Application, Dept of CSE, Sponsored by SRKR Engineering College, June 10th – 15th, 2021. National Seminar Symposia DST-SERB Workshop on Machine Learning Evolve Predictive Data Analytics, Dept of IT, SRKR Engineering College, Sanction Order No: SSY/2017/001121, Sanctioned Date: 13-12-2017, Organized Date:23rd to 28th, July, 2018. Attended numerous Faculty Development Programs and recently received the Recognized Visionary Academic Leadership Award, alongside the Best Faculty Awards from the President of the Artificial Intelligence Medical and Engineering Researchers Society (AIMERS) on March 2, 2024, at CMR Technical Campus, Hyderabad. Additionally, awarded the Dr. A. P. J. Abdul Kalam Global Icon Award and a certificate of appreciation for outstanding contributions as an excellent researcher by Welred Foundation, dated February 28, 2026 (Certificate No: WF/7090/2026).
B.H.V.S. Ramakrishnam Raju is currently the Head of the Department of Computer Science and Engineering and Head of Campus Development at S.R.K.R. Engineering College, Bhimavaram, Andhra Pradesh, India. With over 29 years of rich academic and professional experience in information systems and technologies, he has held several key administrative leadership roles at the institution. He previously served as the Head of the Department of Information Technology, the Dean of Evaluation (2016–2018), and has been the In-charge of the General Computer Centre since 2011. Dr. Raju earned his Ph.D. in Computer Science and Systems Engineering from Andhra University, Visakhapatnam in 2014, where he also completed his M.Tech. in Computer Science and Technology in 2001. Transitioning from a strong foundational background in mechanical engineering, he holds an M.E. from the Birla Institute of Technology (BIT), Mesra, Ranchi (1993) and a Bachelor’s degree from the N.B.K.R. Institute of Science and Technology, Vidyanagar (1989). An active researcher, he has published more than 16 research articles in reputable journals and conference proceedings. Dr. Raju is a recognized professional in his field and holds memberships in the Indian Society for Technical Education (ISTE), the Computer Society of India (CSI), and is a Fellow of the Institution of Engineers (FIE).
G.N.V. Sirisha is an Associate Professor in the Department of Computer Science and Engineering at S.R.K.R. Engineering College, Bhimavaram, with over 21 years of teaching experience and 17 years of research experience. She obtained her B.Tech. in Computer Science and Engineering, M.Tech. in Computer Science and Technology from S.R.K.R. Engineering College and earned her Ph.D. in Computer Science & Systems Engineering from Andhra University. Her research interests include Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Data Mining, and Information Retrieval, Computer Vision. She has published 25 research papers in reputed national and international journals and conferences and has successfully completed two consultancy projects in collaboration with Andhra University. Dr. Sirisha is an active contributor to the research community, serving as a reviewer for international journals and as a Session Chair at conferences focusing on Artificial Intelligence and Computer Science. She has facilitated Faculty Development Programmes and technical training at institutions like JNTUK and Andhra University. In 2025, she shared her expertise in a Certification Course on "Machine Learning and Deep Learning." Additionally, she coordinated various initiatives, including a 100-hour MERN Stack Training Program and workshops on emerging technologies such as Generative AI and Data Science. Dr. Sirisha is also the Programme Coordinator for the B.Tech. AI & ML programme and leads the Quantum Innovation Centre at S.R.K.R. Engineering College.
B.H.V.S. Ramakrishnam Raju is currently the Head of the Department of Computer Science and Engineering and Head of Campus Development at S.R.K.R. Engineering College, Bhimavaram, Andhra Pradesh, India. With over 29 years of rich academic and professional experience in information systems and technologies, he has held several key administrative leadership roles at the institution. He previously served as the Head of the Department of Information Technology, the Dean of Evaluation (2016–2018), and has been the In-charge of the General Computer Centre since 2011. Dr. Raju earned his Ph.D. in Computer Science and Systems Engineering from Andhra University, Visakhapatnam in 2014, where he also completed his M.Tech. in Computer Science and Technology in 2001. Transitioning from a strong foundational background in mechanical engineering, he holds an M.E. from the Birla Institute of Technology (BIT), Mesra, Ranchi (1993) and a Bachelor’s degree from the N.B.K.R. Institute of Science and Technology, Vidyanagar (1989). An active researcher, he has published more than 16 research articles in reputable journals and conference proceedings. Dr. Raju is a recognized professional in his field and holds memberships in the Indian Society for Technical Education (ISTE), the Computer Society of India (CSI), and is a Fellow of the Institution of Engineers (FIE).
G.N.V. Sirisha is an Associate Professor in the Department of Computer Science and Engineering at S.R.K.R. Engineering College, Bhimavaram, with over 21 years of teaching experience and 17 years of research experience. She obtained her B.Tech. in Computer Science and Engineering, M.Tech. in Computer Science and Technology from S.R.K.R. Engineering College and earned her Ph.D. in Computer Science & Systems Engineering from Andhra University. Her research interests include Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Data Mining, and Information Retrieval, Computer Vision. She has published 25 research papers in reputed national and international journals and conferences and has successfully completed two consultancy projects in collaboration with Andhra University. Dr. Sirisha is an active contributor to the research community, serving as a reviewer for international journals and as a Session Chair at conferences focusing on Artificial Intelligence and Computer Science. She has facilitated Faculty Development Programmes and technical training at institutions like JNTUK and Andhra University. In 2025, she shared her expertise in a Certification Course on "Machine Learning and Deep Learning." Additionally, she coordinated various initiatives, including a 100-hour MERN Stack Training Program and workshops on emerging technologies such as Generative AI and Data Science. Dr. Sirisha is also the Programme Coordinator for the B.Tech. AI & ML programme and leads the Quantum Innovation Centre at S.R.K.R. Engineering College.
Descriere
This book connects theoretical concepts with practical applications in Advanced Artificial Intelligence, serving academic, research, and industrial needs. ICAAAI-2025 is a key forum uniting researchers, academicians, industry experts, and students to discuss advancements in AI algorithms and intelligent computing.