ReviewAnimals : an open access journal from MDPI2021
Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review.
Review in Animals : an open access journal from MDPI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Integrated approaches for lameness control in free-stall dairy systems under heat stress and water scarcity.Tropical animal health and production · 2026Review
- GADF-enhanced global-local feature network for wearable sensor-based cow behavior recognition.Frontiers in veterinary science · 2026Article
- Direct video-based spatiotemporal deep learning for cattle lameness detection.Scientific reports · 2025Article
- Real-Time Auto-Monitoring of Livestock: Quantitative Framework and Challenges.Sensors (Basel, Switzerland) · 2025Review
- Wearable Sensors-Based Intelligent Sensing and Application of Animal Behaviors: A Comprehensive Review.Sensors (Basel, Switzerland) · 2025Review
- AI and Data Analytics in the Dairy Farms: A Scoping Review.Animals : an open access journal from MDPI · 2025Review
- Comparison of machine learning and validation methods for high-dimensional accelerometer data to detect foot lesions in dairy cattle.PloS one · 2025Article
- Cloud-edge-device collaborative computing in smart agriculture: architectures, applications, and future perspectives.Frontiers in plant science · 2025Review
- Welfare indicators in cattle farming in the face of heat stress: a review in climate change scenarios.Frontiers in veterinary science · 2025Article
- Impact of Feed Bunk Space on the Prevalence of Torsion and Foreleg Distal Asymmetry in Holstein Cows.Animals : an open access journal from MDPI · 2024Article
- Intelligent weight prediction of cows based on semantic segmentation and back propagation neural network.Frontiers in artificial intelligence · 2024Article
- Review
- Nanotechnology and E-Sensing for Food Chain Quality and Safety.Sensors (Basel, Switzerland) · 2023Review
- A workflow for automatic, high precision livestock diagnostic screening of locomotor kinematics.Frontiers in veterinary science · 2023Article
- Double-Camera Fusion System for Animal-Position Awareness in Farming Pens.Foods (Basel, Switzerland) · 2022Article
- The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming.Sensors (Basel, Switzerland) · 2022Review
- Postural behavior recognition of captive nocturnal animals based on deep learning: a case study of Bengal slow loris.Scientific reports · 2022Article
- Holstein Cattle Face Re-Identification Unifying Global and Part Feature Deep Network with Attention Mechanism.Animals : an open access journal from MDPI · 2022Article
- One-Shot Learning with Pseudo-Labeling for Cattle Video Segmentation in Smart Livestock Farming.Animals : an open access journal from MDPI · 2022Article
- Deep Learning Based Automatic Grape Downy Mildew Detection.Frontiers in plant science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The growing world population has increased the demand for animal-sourced protein. However, animal farming productivity is faced with challenges from traditional farming practices, socioeconomic status, and climate change. In recent years, smart sensors, big data, and deep learning have been applied to animal welfare measurement and livestock farming applications, including behaviour recognition and health monitoring. In order to facilitate research in this area, this review summarises and analyses some main techniques used in smart livestock farming, focusing on those related to cattle lameness detection and behaviour recognition. In this study, more than 100 relevant papers on cattle lameness detection and behaviour recognition have been evaluated and discussed. Based on a review and a comparison of recent technologies and methods, we anticipate that intelligent perception for cattle behaviour and welfare monitoring will develop towards standardisation, a larger scale, and intelligence, combined with Internet of things (IoT) and deep learning technologies. In addition, the key challenges and opportunities of future research are also highlighted and discussed.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.