Intelligent Surveillance of Marine Objects using Deep Learning

1. Auflage 2027
ISBN: 978-1-394-43269-1
Verlag: John Wiley & Sons Inc

Buch, Englisch, 304 Seiten

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 models
- Analysis of performance metrics enabling direct comparison of marine object detection approaches across multiple published research works
- Coverage of environmental challenges unique to underwater imaging including turbidity, dynamic currents, camouflage, and occlusion effects
- Examination of marine object detection applications in high-security ocean surveillance, defense systems, and autonomous underwater vehicle platforms
- Alignment 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.

Autoren/Hrsg.

Kumar, Ashish

Über Autor(innen)

Ashish Kumar is a Professor in the School of Computer Science Engineering and Technology at Bennett University, Greater Noida, Uttar Pradesh, India. His research focuses on deep learning approaches to marine object detection, underwater image analysis, and AI-driven surveillance systems for challenging aquatic environments.

Shikha Bhalla is a Lecturer in computer vision and machine learning at Guru Tegh Bahadur Institute of Technology, New Delhi, India. Her work centers on applying machine learning and computer vision techniques to real-world detection and classification tasks in complex visual environments.