ArticleSensors (Basel, Switzerland)2019
Multi-Pig Part Detection and Association with a Fully-Convolutional Network.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Practices and Applications of Convolutional Neural Network-Based Computer Vision Systems in Animal Farming: A Review.Sensors (Basel, Switzerland) · 2021Pooled it
- StaticPigDetv2: Performance Improvement of Unseen Pig Monitoring Environment Using Depth-Based Background and Facility Information.Sensors (Basel, Switzerland) · 2026Article
- Genetic Heterogeneity of Residual Variance for Foot Score Traits in American Angus Cattle.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Continuous NUTranslational animal science · 2026Article
- Low-Altitude UAV-Based Recognition of Porcine Facial Expressions for Early Health Monitoring.Animals : an open access journal from MDPI · 2025Article
- An Automatic Ear Temperature Monitoring Method for Group-Housed Pigs Adopting Infrared Thermography.Animals : an open access journal from MDPI · 2025Article
- Enhanced YOLOv8 for Robust Pig Detection and Counting in Complex Agricultural Environments.Animals : an open access journal from MDPI · 2025Article
- Sustainable Self-Training Pig Detection System with Augmented Single Labeled Target Data for Solving Domain Shift Problem.Sensors (Basel, Switzerland) · 2025Article
- Genomic analysis of mobility measures on 5-month-old gilts associated with structural soundness.Journal of animal science · 2025Article
- GooseDetectScientific data · 2024Article
- Pixel Self-Attention Guided Real-Time Instance Segmentation for Group Raised Pigs.Animals : an open access journal from MDPI · 2023Article
- Identifying Early-Life Behavior to Predict Mothering Ability in Swine Utilizing NUAnimals : an open access journal from MDPI · 2023Article
- YOLOv5-KCB: A New Method for Individual Pig Detection Using Optimized K-Means, CA Attention Mechanism and a Bi-Directional Feature Pyramid Network.Sensors (Basel, Switzerland) · 2023Article
- Utilizing NUAnimals : an open access journal from MDPI · 2023Article
- Evaluation of Precision Livestock Technology and Human Scoring of Nursery Pigs in a Controlled Immune Challenge Experiment.Animals : an open access journal from MDPI · 2023Article
- StaticPigDet: Accuracy Improvement of Static Camera-Based Pig Monitoring Using Background and Facility Information.Sensors (Basel, Switzerland) · 2022Article
- Evaluation of a novel computer vision-based livestock monitoring system to identify and track specific behaviors of individual nursery pigs within a group-housed environment.Translational animal science · 2022Article
- EmbeddedPigCount: Pig Counting with Video Object Detection and Tracking on an Embedded Board.Sensors (Basel, Switzerland) · 2022Article
- Detecting Animal Contacts-A Deep Learning-Based Pig Detection and Tracking Approach for the Quantification of Social Contacts.Sensors (Basel, Switzerland) · 2021Article
- Welfare Health and Productivity in Commercial Pig Herds.Animals : an open access journal from MDPI · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Computer vision systems have the potential to provide automated, non-invasive monitoring of livestock animals, however, the lack of public datasets with well-defined targets and evaluation metrics presents a significant challenge for researchers. Consequently, existing solutions often focus on achieving task-specific objectives using relatively small, private datasets. This work introduces a new dataset and method for instance-level detection of multiple pigs in group-housed environments. The method uses a single fully-convolutional neural network to detect the location and orientation of each animal, where both body part locations and pairwise associations are represented in the image space. Accompanying this method is a new dataset containing 2000 annotated images with 24,842 individually annotated pigs from 17 different locations. The proposed method achieves over 99% precision and over 96% recall when detecting pigs in environments previously seen by the network during training. To evaluate the robustness of the trained network, it is also tested on environments and lighting conditions unseen in the training set, where it achieves 91% precision and 67% recall. The dataset is publicly available for download.
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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.