Deep Learning in Genome Mapping
Computation and Analysis
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Product details:
- Edition number 1
- Publisher CRC Press
- Date of Publication 5 March 2026
- ISBN 9781032833811
- Binding Hardback
- No. of pages218 pages
- Size 234x156 mm
- Weight 453 g
- Language English
- Illustrations 55 Illustrations, black & white; 11 Illustrations, color; 13 Halftones, black & white; 3 Halftones, color; 42 Line drawings, black & white; 8 Line drawings, color; 19 Tables, black & white 700
Categories
Short description:
This book explores advanced methodologies and empirical research in machine learning through data mining and GPU-based parallel programming. It highlights the integration of modern deep learning techniques with CUDA architecture for efficient big data processing.
MoreLong description:
The book aims to develop methodologies and throw light on the advances in empirical research of various machine learning systems through data mining and parallel programming using GPU approaches. It reviews concepts of existing machine learning and deep learning techniques and how these can be implemented in GPU computing with CUDA architecture. The book also discusses modern machine learning techniques for effective big data management in accordance with worldwide standards in the field.
Covering diverse areas, this publication is meant for academicians, data scientists, industrial professionals, researchers and students interested in uncovering the latest innovations in the field.
MoreTable of Contents:
Preface. Computation and Analysis for Genome Mapping using the Deep Learning-based Optimization Algorithm. Prediction for Genome Mapping with the Multi-objective Evolutionary Algorithm. Deep Learning and Medical Data Engineering for Knowledge Discovery. Integrating DL Techniques for Precise Genome Mapping: Methods and Applications. Analysing Genomes using Deep Learning and Image Processing Techniques. Introduction to Neural network and Machine Learning as a Subset of AI. Advancing Smart Healthcare: Enhanced Image Analysis and Feature Extraction through Integration of Sharpening Techniques and Edge Detection Algorithms. Optimizing Noise Reduction Strategies in Medical Imaging through Advanced Techniques and Performance Evaluation Metrics. Revolutionizing Medicine: Machine Learning Innovations in Medical Science. Development and Validation of an AI-Based Model for Heart Delineation in Chest X-Ray Images. Index.
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