An Attention Mechanism-Improved YOLOv7 Object Detection Algorithm for Hemp Duck Count Estimation

Article Engineering, Multidisciplinary

ChickTrack-A quantitative tracking tool for measuring chicken activity

Suresh Neethirajan

Summary: This paper proposes a deep learning-based method for detecting and tracking domesticated chickens in complex backgrounds. The method utilizes multiscale features and Kalman Filter to achieve real-time tracking of multiple chickens in videos, providing accurate counting and trajectory measurements.

MEASUREMENT (2022)

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Article Agronomy

Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5

Yue Gu et al.

Summary: This study used machine vision technology for automatic recognition of important behaviors of cage-reared ducks, and found that the neck extension, trampling, and wing spread behaviors of laying ducks significantly increase when they feel panic and fear.

AGRICULTURE-BASEL (2022)

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Article Agriculture, Dairy & Animal Science

Classification of broiler behaviours using triaxial accelerometer and machine learning

X. Yang et al.

Summary: Understanding broiler behaviours through wearable accelerometers and machine learning models can effectively classify specific behaviors, with varying performances of different models. A window length of 1 second yields the best performance for classifying continuous broiler behaviors.

ANIMAL (2021)

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Review Computer Science, Artificial Intelligence

A review on the attention mechanism of deep learning

Zhaoyang Niu et al.

Summary: This paper provides an overview of state-of-the-art attention models and defines a unified model suitable for most attention structures. It describes in detail each step of the attention mechanism implemented in the model and classifies existing attention models based on four criteria. Additionally, it summarizes the use of attention mechanisms in network architectures and typical applications.

NEUROCOMPUTING (2021)

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Article Chemistry, Analytical