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{ "item_title" : "Deep Learning Methods Image Object Detection & Recognition", "item_author" : [" Shi Pengfei "], "item_description" : "This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restoration-including UNet-based defogging, feature fusion GANs, and ESRGAN super-resolution-alongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/81/983/334/9819833345_b.jpg", "price_data" : { "retail_price" : "98.00", "online_price" : "98.00", "our_price" : "98.00", "club_price" : "98.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Deep Learning Methods Image Object Detection & Recognition|Shi Pengfei

Deep Learning Methods Image Object Detection & Recognition

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Overview

This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restoration-including UNet-based defogging, feature fusion GANs, and ESRGAN super-resolution-alongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation.

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Details

  • ISBN-13: 9789819833344
  • ISBN-10: 9819833345
  • Publisher: World Scientific Publishing Company
  • Publish Date: July 2026
  • Dimensions: 9 x 6 x 0.81 inches
  • Shipping Weight: 1.4 pounds
  • Page Count: 258

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