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{ "item_title" : "Machine Vision Empowered Intelligent Large-scale Waterfowl Farming", "item_author" : [" Shida Zhao "], "item_description" : "In recent years, the large-scale farming of commercial meat ducks has rapidly transitioned toward automation and digital intelligence. However, challenges such as occlusion, behavior ambiguity, and posture variability under intensive cage-rearing systems have hindered accurate perception and management of animal welfare. Machine Vision Empowered Intelligent Large-scale Waterfowl Farming provides a comprehensive exploration of vision-based intelligent technologies for behavior recognition and posture estimation in commercial meat ducks. By integrating deep learning, image processing, and sensor fusion, this book establishes an end-to-end framework that enables precise monitoring and intelligent decision-making in waterfowl production systems. The book systematically introduces the theoretical foundations of computer vision, the development of duck detection and segmentation algorithms, and the design of multi-keypoint posture estimation models. It also details the construction of real-time monitoring platforms and autonomous inspection robots for modern duck houses. Through innovative research on occlusion compensation, multi-scene adaptability, and fine-grained behavior understanding, the work bridges the gap between algorithmic innovation and engineering application in intelligent poultry farming. This volume serves as a valuable reference for researchers, engineers, and graduate students engaged in animal behavior analysis, precision livestock farming, and agricultural intelligent equipment design. Looking forward, it envisions a future of sustainable and welfare-oriented waterfowl farming, where machine vision and artificial intelligence jointly empower intelligent perception and management.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/99/933/212/9999332129_b.jpg", "price_data" : { "retail_price" : "45.50", "online_price" : "45.50", "our_price" : "45.50", "club_price" : "45.50", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Vision Empowered Intelligent Large-scale Waterfowl Farming|Shida Zhao

Machine Vision Empowered Intelligent Large-scale Waterfowl Farming

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Overview

In recent years, the large-scale farming of commercial meat ducks has rapidly transitioned toward automation and digital intelligence. However, challenges such as occlusion, behavior ambiguity, and posture variability under intensive cage-rearing systems have hindered accurate perception and management of animal welfare. Machine Vision Empowered Intelligent Large-scale Waterfowl Farming provides a comprehensive exploration of vision-based intelligent technologies for behavior recognition and posture estimation in commercial meat ducks. By integrating deep learning, image processing, and sensor fusion, this book establishes an end-to-end framework that enables precise monitoring and intelligent decision-making in waterfowl production systems. The book systematically introduces the theoretical foundations of computer vision, the development of duck detection and segmentation algorithms, and the design of multi-keypoint posture estimation models. It also details the construction of real-time monitoring platforms and autonomous inspection robots for modern duck houses. Through innovative research on occlusion compensation, multi-scene adaptability, and fine-grained behavior understanding, the work bridges the gap between algorithmic innovation and engineering application in intelligent poultry farming. This volume serves as a valuable reference for researchers, engineers, and graduate students engaged in animal behavior analysis, precision livestock farming, and agricultural intelligent equipment design. Looking forward, it envisions a future of sustainable and welfare-oriented waterfowl farming, where machine vision and artificial intelligence jointly empower intelligent perception and management.

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Details

  • ISBN-13: 9789999332125
  • ISBN-10: 9999332129
  • Publisher: Eliva Press
  • Publish Date: January 2025
  • Dimensions: 9 x 6 x 0.19 inches
  • Shipping Weight: 0.29 pounds
  • Page Count: 90

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