A systematic literature review on deep learning applications for precision cattle farming

Detection of the respiratory rate of standing cows by combining the Deeplab V3+ semantic segmentation model with the phase-based video magnification algorithm

(2020) Dihua Wu et al.   BIOSYSTEMS ENGINEERING

Cow identification based on fusion of deep parts features

(2020) Hengqi Hu et al.   BIOSYSTEMS ENGINEERING

Assessment of dairy cow heat stress by monitoring drinking behaviour using an embedded imaging system

(2020) Yu-Chi Tsai et al.   BIOSYSTEMS ENGINEERING

Computer vision system for measuring individual cow feed intake using RGB-D camera and deep learning algorithms

(2020) Ran Bezen et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Automated cattle counting using Mask R-CNN in quadcopter vision system

(2020) Beibei Xu et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Counting Cattle in UAV Images—Dealing with Clustered Animals and Animal/Background Contrast Changes

(2020) Jayme Garcia Arnal Barbedo et al.   SENSORS

Single-stream long-term optical flow convolution network for action recognition of lameness dairy cow

(2020) Bo Jiang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Recognition of Pantaneira cattle breed using computer vision and convolutional neural networks

(2020) Fabricio de Lima Weber et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

FSSCaps-DetCountNet: fuzzy soft sets and CapsNet-based detection and counting network for monitoring animals from aerial images

(2020) Divya Meena Sundaram et al.   Journal of Applied Remote Sensing

A review on dairy cattle farming: Is precision livestock farming the compromise for an environmental, economic and social sustainable production?

(2020) Daniela Lovarelli et al.   JOURNAL OF CLEANER PRODUCTION

Automatic Cow Location Tracking System Using Ear Tag Visual Analysis

(2020) Thi Thi Zin et al.   SENSORS

Image analysis for individual identification and feeding behaviour monitoring of dairy cows based on Convolutional Neural Networks (CNN)

(2020) Brahim Achour et al.   BIOSYSTEMS ENGINEERING

Deep learning-based hierarchical cattle behavior recognition with spatio-temporal information

(2020) Alvaro Fuentes et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Using an EfficientNet-LSTM for the recognition of single Cow’s motion behaviours in a complicated environment

(2020) Xuqiang Yin et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

A computer vision approach to improving cattle digestive health by the monitoring of faecal samples

(2020) Gary A. Atkinson et al.   Scientific Reports

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

(2020) Michael A. Tabak et al.   Ecology and Evolution

A systematic literature review on the use of machine learning in precision livestock farming

(2020) Rodrigo García et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Development and validation of a neural network for the automated detection of horn flies on cattle

(2020) E.T. Psota et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Instance Segmentation with Mask R-CNN Applied to Loose-Housed Dairy Cows in a Multi-Camera Setting

(2020) Jennifer Salau et al.   Animals

Application of machine learning to improve dairy farm management: A systematic literature review

(2020) Naftali Slob et al.   PREVENTIVE VETERINARY MEDICINE

Individual identification of dairy cows based on convolutional neural networks

(2019) Weizheng Shen et al.   MULTIMEDIA TOOLS AND APPLICATIONS

Cattle detection and counting in UAV images based on convolutional neural networks

(2019) Wen Shao et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

An Improved Single Shot Multibox Detector Method Applied in Body Condition Score for Dairy Cows

(2019) Xiaoping Huang et al.   Animals

Deep cascaded convolutional models for cattle pose estimation

(2019) Xiangyuan Li et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Cattle segmentation and contour extraction based on Mask R-CNN for precision livestock farming

(2019) Yongliang Qiao et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

FLYOLOv3 deep learning for key parts of dairy cow body detection

(2019) Bo Jiang et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Automatic monitoring system for individual dairy cows based on a deep learning framework that provides identification via body parts and estimation of body condition score

(2019) Sun Yukun et al.   JOURNAL OF DAIRY SCIENCE

Body Dimension Measurements of Qinchuan Cattle with Transfer Learning from LiDAR Sensing

(2019) Lvwen Huang et al.   SENSORS

Lameness detection of dairy cows based on the YOLOv3 deep learning algorithm and a relative step size characteristic vector

(2019) Dihua Wu et al.   BIOSYSTEMS ENGINEERING

A Study on the Detection of Cattle in UAV Images Using Deep Learning

(2019) Jayme Garcia Arnal Barbedo et al.   SENSORS

Mismatch between food sustainability and consumer acceptance toward innovation technologies among Millennial students: The case of Shelf Life Extension

(2018) Alessia Cavaliere et al.   JOURNAL OF CLEANER PRODUCTION

Deep learning framework for recognition of cattle using muzzle point image pattern

(2018) Santosh Kumar et al.   MEASUREMENT

Detection of Cattle Using Drones and Convolutional Neural Networks

(2018) Alberto Rivas et al.   SENSORS

Machine learning to classify animal species in camera trap images: Applications in ecology

(2018) Michael A. Tabak et al.   Methods in Ecology and Evolution

Editorial: Precision livestock farming: a ‘per animal’ approach using advanced monitoring technologies

(2016) I. Halachmi et al.   Animal

Sound analysis in dairy cattle vocalisation as a potential welfare monitor

(2015) G.H. Meen et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Agent-based simulation framework for virtual prototyping of advanced livestock precision feeding systems

(2011) J. Pomar et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Food Security: The Challenge of Feeding 9 Billion People

(2010) H. C. J. Godfray et al.   SCIENCE

Empirical evidence in global software engineering: a systematic review

(2009) Darja Šmite et al.   EMPIRICAL SOFTWARE ENGINEERING