Search research articles

关于 JoVE

概览领导团队博客 JoVE 帮助中心

作者

出版流程编辑委员会范围与政策同行评审常见问题投稿

图书馆员

用户评价订阅访问资源图书馆顾问委员会常见问题

研究

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments 存档

教育

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual 教师资源中心教师网站

使用条款与条件

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序

Same author

Stable and High-Throughput Single-Cell Sorting of Food Bacteria Using Spatiotemporal Video-Enhanced Raman Tweezers.

Foods (Basel, Switzerland)·2026

Same author

Cardiorespiratory Fitness Reference Standards and Prognostic Stratification in Chinese Patients With Cardiovascular Disease.

JACC. Asia·2026

Same author

Predictive Equation for Peak Heart Rate and First Ventilatory Threshold Heart Rate in Patients With Coronary Heart Disease.

Cardiology research and practice·2026

Same author

Near Full-Length Genome Characterization of a Novel Second-Generation HIV-1 CRF01_AE/CRF07_BC Recombinant Identified in an MSM Individual in Guizhou, China.

AIDS research and human retroviruses·2026

Same author

Case Report: Ivarmacitinib in the treatment of refractory primary cutaneous amyloidosis.

Frontiers in medicine·2026

Same author

A recombinant goat pox virus expressing the Brucella OMP25 antigen conferring moderate protection against B. abortus in mice.

Vaccine·2026

Search research articles

相关实验视频

Updated: Jun 25, 2025

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

Published on: September 7, 2015

牛的多目标养行为识别方法基于改进的RefineMask.

Xuwen Li^1,2, Ronghua Gao^1,2, Qifeng Li^1,2

¹College of Computer and Information Engineering, Tianjin Agricultural University, Tianjin 300384, China.

Sensors (Basel, Switzerland)

|May 25, 2024

概括

这项研究引入了一种改进的RefineMask模型,用于准确识别奶牛的养行为. 改进后的模型达到98.3%的准确性,为畜牧管理提供了强大的视觉分析.

关键词:

精细化面具面具精细化行为识别行为识别.养行为养行为实例细分实例细分实例细分

更多相关视频

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Published on: August 16, 2024

The Use of Traditional Fear Tests to Evaluate Different Emotional Circuits in Cattle

The Use of Traditional Fear Tests to Evaluate Different Emotional Circuits in Cattle

Published on: April 22, 2020

相关实验视频

Last Updated: Jun 25, 2025

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

Published on: September 7, 2015

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Integration of Animal Behavioral Assessment and Convolutional Neural Network to Study Wasabi-Alcohol Taste-Smell Interaction

Published on: August 16, 2024

The Use of Traditional Fear Tests to Evaluate Different Emotional Circuits in Cattle

The Use of Traditional Fear Tests to Evaluate Different Emotional Circuits in Cattle

Published on: April 22, 2020

科学领域:

农业科学农业科学
计算机视觉计算机视觉
动物行为动物行为

背景情况:

目前的乳牛养殖依赖于视觉方法来识别行为,通常受到低准确度和高错误率的限制.
精确监测奶牛的养行为对于了解料摄入量和优化群体管理至关重要.

研究的目的:

使用改进的实例分割模型开发乳牛养行为先进的视觉识别方法.
提高在大型繁殖业务中检测和细分牛养活动的准确性和稳定性.

主要方法:

开发了一种改进的RefineMask实例细分模型,结合了卷积块注意力和高效通道注意力模块.
该模型利用GIoU损失来提高界限框回归准确度,并为搜索行为识别提供掩盖信息.
为了培训和测试,创建了一个由50只奶牛在养高峰时间拍摄的1000张图像的数据集.

主要成果:

改进的RefineMask算法在界限框识别和细分面具确定中实现了98.3%的准确性.
这种准确性比基准模型高0.7个百分点,模型尺寸为49.96M,适合当地部署.
该方法在各种场景和照明条件中表现出稳健性.

结论:

提出的基于RefineMask的方法显著提高了奶牛养行为识别的准确性和可靠性.
这项技术为分析牛养行为与料摄入量之间的关系提供了宝贵的技术支持.
这些发现有助于更高效和数据驱动的乳牛养殖和管理实践.