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Intelligent Surveillance of Marine Objects using Deep Learning
Deep learning techniques for marine object detection in challenging underwater environments Underwater environments present unique detection challenges: reduced brightness, haziness, colour variation, water turbidity, dynamic currents, camouflaged organisms, occlusion, and extreme size variation. Underwater Marine Object Dete......
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Deep learning techniques for marine object detection in challenging underwater environments Underwater environments present unique detection challenges: reduced brightness, haziness, colour variation, water turbidity, dynamic currents, camouflaged organisms, occlusion, and extreme size variation. Underwater Marine Object Detection Using Deep Learning addresses these obstacles by surveying recently developed AI techniques for marine object detection and classification. Authored by Ashish Kumar and Shikha Bhalla, this reference consolidates detection pipelines, public datasets, and performance benchmarks into a single authoritative volume. The book provides exhaustive analysis of existing marine object datasets evaluated against real-time detection challenges. Performance metrics used across published works are systematically reviewed for direct comparison. Coverage extends to detect and analyse the life below water that aligns with UN Sustainable Development Goal 14 for marine protection. Applications span ecological monitoring, underwater robotics, pipeline detection, underwater archaeology, and defence operations. Readers will also find: Systematic review of public underwater image datasets with assessment of their potential for improving AI-based detection modelsAnalysis of performance metrics enabling direct comparison of marine object detection approaches across multiple published research worksCoverage of environmental challenges unique to underwater imaging including turbidity, dynamic currents, camouflage, and occlusion effectsExamination of marine object detection applications in high-security ocean surveillance, defense systems, and autonomous underwater vehicle platformsAlignment with SDG 14 sustainability goals connecting AI-driven detection techniques to broader marine ecosystem protection and conservation efforts Designed for marine scientists, AI researchers, PhD and postgraduate students, and professionals in underwater object detection, this book serves as a consolidated reference for building robust detection and classification models. Defence and industry R&D units operating AUV and ROV platforms will find the systematic coverage of detection pipelines directly applicable to operational requirements.
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| Produkt | |
|---|---|
| Produktnavn | Intelligent Surveillance of Marine Objects using Deep Learning |
| Merke | Other Brand |
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