{"product_id":"machine-learning-image-processing-network-security-and-data-sciences-gyanendra-k-ebook-1","title":"Machine Learning, Image Processing, Network Security and Data Sciences","description":"\u003cp\u003e\u003cstrong\u003e.- Artificial Intelligence and Intelligent Systems.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e.- Visual and Local Explanations for Trustworthy AI for Autism Detection for Asian Data.\u003c\/p\u003e\n\u003cp\u003e.- Hybrid Graph–Language Embedding Framework for Citation-Aware Sentiment \u003cbr\u003eAnalysis.\u003c\/p\u003e\n\u003cp\u003e.- AI-driven Anomaly Detection in Avionics Systems using Isolation Forest.\u003c\/p\u003e\n\u003cp\u003e.-  Integrating Postmortem Reports and Embedding Techniques for Fault Prediction.\u003c\/p\u003e\n\u003cp\u003e.- Coverage  Precision  and Fairness in Association-Rule Mining: Evidence from \u003cbr\u003eTreadmill.\u003c\/p\u003e\n\u003cp\u003e.-  Demonstrating Quantum Advantage in GANs: A Comparative Study on Diabetes \u003cbr\u003eHealthcare Data.\u003c\/p\u003e\n\u003cp\u003e.-  A Hybrid Deep Learning Approach for Automated Plant Disease Diagnosis in Indian \u003cbr\u003eRidge Gourd: Dataset Creation and Real-World Application.\u003c\/p\u003e\n\u003cp\u003e.- Experimental Study on Tea Plant Disease Classification.\u003c\/p\u003e\n\u003cp\u003e.- Multiscale Recursive Attention Guided Deep Feature Fusion Network for Haze \u003cbr\u003eRemoval.\u003c\/p\u003e\n\u003cp\u003e.- Deepfake Video Detection using CNN Deep Learning Architectures.\u003c\/p\u003e\n\u003cp\u003e.- Crop-Specific Hyperparameter Optimization for Machine Learning-Based Yield \u003cbr\u003ePrediction of Kharif Crops: Rice  Wheat  and Maize.\u003c\/p\u003e\n\u003cp\u003e.- Enhancing Real-Time Through-Wall Imaging with a Hybrid Signal Processing and \u003cbr\u003eConvolutional Neural Network Approach.\u003c\/p\u003e\n\u003cp\u003e.- Advanced Kalman Filtering for Video-Based Tremor Assessment in Parkinson’s \u003cbr\u003eChapter 1. Disease: Comparative Analysis with Deep Learning Classification.\u003c\/p\u003e\n\u003cp\u003e.- LightGraph: Efficient Multi-modal Sparse Graph Attention Network for Crisis \u003cbr\u003eTweet Classification.\u003c\/p\u003e\n\u003cp\u003e.-  TTMFN: A Time-aware Transformer-based Multimodal Fusion Network for \u003cbr\u003eDepression Detection from Social Media.\u003c\/p\u003e\n\u003cp\u003e.- Synthetic Images Generation for Skin Cancer Using Conditional Generative \u003cbr\u003eAdversarial Network with Explanation.\u003c\/p\u003e\n\u003cp\u003e.- Evaluating Privacy Risks in Machine Unlearning: A Comprehensive Audit of \u003cbr\u003eUnlearned and Retained Samples.\u003c\/p\u003e\n\u003cp\u003e.- Adaptive Edge-Cloud Orchestration: A Serverless Paper on Intelligent ML \u003cbr\u003eApplication Placement with Hybrid Resource Feedback.\u003c\/p\u003e\n\u003cp\u003e.-  Explainable Mortality Outcome Prediction Using Neuro-Symbolic Causal \u003cbr\u003eReasoning.\u003c\/p\u003e\n\u003cp\u003e.-  Enhanced Class Imbalance-Aware Skin Cancer Classification.\u003c\/p\u003e\n\u003cp\u003e.- Glaucoma detection using deep learning.\u003c\/p\u003e\n\u003cp\u003e.- Temporal Stability in Semi-Supervised Label Propagation: A Lightweight \u003cbr\u003eRegularization Framework.\u003c\/p\u003e\n\u003cp\u003e.- Enhancing Cardiovascular Care Using IoT Data and CatBoost Machine Learning \u003cbr\u003eModel.\u003c\/p\u003e\n\u003cp\u003e.-  Image-Based Multi-Class Classification of Diabetic Retinopathy Using Deep \u003cbr\u003eLearning.\u003c\/p\u003e\n\u003cp\u003e.-  MoTANet: A Hybrid MobileNetV2–Transformer Attention Network for Multi-Crop \u003cbr\u003eDisease Classification.\u003c\/p\u003e\n\u003cp\u003e.- Ano-HQNN: Hybrid Quantum Neural Network for Enhanced Anomaly Detection in \u003cbr\u003eSurveillance Videos.\u003c\/p\u003e\n\u003cp\u003e.-  Efficient Handwriting Recognition for Person  Identification Using Lightweight \u003cbr\u003eand Deep CNN  Model.\u003c\/p\u003e\n\u003cp\u003e.- Choosing the Right Optimizer and Loss Function: A Deep Learning Perspective on \u003cbr\u003eHyperspectral Image Classification.\u003c\/p\u003e\n\u003cp\u003e.- A Lightweight LiDAR-Only Path Planning Framework for Formula Student \u003cbr\u003eDriverless Racecar.\u003c\/p\u003e\n\u003cp\u003e.-  Bridging the Communication Divide: Sign  Language in Online Meetings  Kulkarni.\u003c\/p\u003e\n\u003cp\u003e.- Transformer-Enhanced Residual U-Net for Automated Dental Plaque \u003cbr\u003eSegmentation in Clinical Intraoral Imagery.\u003c\/p\u003e\n\u003cp\u003e.- DEV3NET: A Two-Stage Deep Learning Approach for Automated Occlusion Mask \u003cbr\u003eGeneration and Facial Segmentation.\u003c\/p\u003e\n\u003cp\u003e.- Deepfake Face Detection using an Ensemble of Multiple Deep Learning Models  \u003cbr\u003eKavad  Meet.\u003c\/p\u003e\n\u003cp\u003e.-  Knowledge-Grounded Canonical SMILES Generation via RAG-enhanced Large \u003cbr\u003eLanguage Models.\u003c\/p\u003e\n\u003cp\u003e.- A Mastery-Guided Retrieval-Augmented Generation for Grounded Tutoring.\u003c\/p\u003e\n\u003cp\u003e.-  Data-Driven Rockfall Assessment using Synthetic Training and CNN–XGBoost \u003cbr\u003eIntegration.\u003c\/p\u003e\n\u003cp\u003e.- SpeechComp-FSQ: A Transformer-Based Model for Efficient Speech Compression.\u003c\/p\u003e\n\u003cp\u003e.- Ensemble Deep Learning with a Trainable Meta-Learner for Enhanced Semantic \u003cbr\u003eSegmentation of Informal Settlements.\u003c\/p\u003e\n\u003cp\u003e.- Linguistic Network Analysis of Psychopathology Dimensions in Adolescence: A \u003cbr\u003eCognitive Neuropsychological Approach.\u003c\/p\u003e\n\u003cp\u003e.-  Cross Attentive Multimodal Fusion Network Using Deep Learning Models and \u003cbr\u003eTransformers for Driver Drowsiness Detection.\u003c\/p\u003e\n\u003cp\u003e.- Human Pose Estimation for Cricket Shot Classification: Machine Learning and \u003cbr\u003eDeep Learning Perspectives.\u003c\/p\u003e\n\u003cp\u003e.-  Automated Seizure Classification from Raw Intracranial EEG Using a Transformer \u003cbr\u003eEncoder.\u003c\/p\u003e\n\u003cp\u003e.-  A Multi-Metric Decomposed Mode Selection for Phase-Based EEG Recurrence \u003cbr\u003eAnalysis in Major Depressive Disorder (INVITED).\u003c\/p\u003e","brand":"Gyanendra Kumar Verma","offers":[{"title":"Default Title","offer_id":55096355750215,"sku":"9783032312334","price":171.19,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/files\/machine-learning-image-processing-network-security-ebook-cover-gyanendra-kumar-verma.webp?v=1789882068","url":"https:\/\/www.cinebuch.de\/products\/machine-learning-image-processing-network-security-and-data-sciences-gyanendra-k-ebook-1","provider":"CineBuch","version":"1.0","type":"link"}