ArticleScientific reports2021
Zebrafish tracking using YOLOv2 and Kalman filter.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Article
- StrIPETrack: a real-time, ROI-flexible tracking platform for high-throughput zebrafish behavior.Biology open · 2026Article
- High-throughput multi-camera array microscope platform for automated 3D behavioral analysis of swimming zebrafish larvae.Communications biology · 2026Article
- Zebrafish as a multimodal platforms for anti-inflammatory phytomedicine discovery and translation.Frontiers in pharmacology · 2026Review
- High-throughput multi-camera array microscope platform for automated 3D behavioral analysis of swimming zebrafish larvae.bioRxiv : the preprint server for biology · 2025Article
- Synergistic enhancement of detection-tracking framework for zebrafish shoaling behavior analysis.Scientific reports · 2025Article
- An Analysis of the Movement Trajectories of the EndangeredAnimals : an open access journal from MDPI · 2025Article
- Applying deep learning and the ecological home range concept to document the spatial distribution of Atlantic salmon parr (Salmo salar L.) in experimental tanks.Scientific reports · 2025Article
- Animal re-identification in video through track clustering.Pattern analysis and applications : PAA · 2025Article
- Identification and Counting of PirapitingaAnimals : an open access journal from MDPI · 2024Article
- Large Span Sizes and Irregular Shapes Target Detection Methods Using Variable Convolution-Improved YOLOv8.Sensors (Basel, Switzerland) · 2024Article
- Exploring the use of deep learning models for accurate tracking of 3D zebrafish trajectories.Frontiers in bioengineering and biotechnology · 2024Article
- Unlocking the Potential of Zebrafish Research with Artificial Intelligence: Advancements in Tracking, Processing, and Visualization.Medical & biological engineering & computing · 2023Review
- Integrated software for multi-dimensional analysis of motion using tracking, electrophysiology, and sensor signals.Frontiers in bioengineering and biotechnology · 2023Article
- Marker-less tracking system for multiple mice using Mask R-CNN.Frontiers in behavioral neuroscience · 2022Article
- Parallel Fish School Tracking Based on Multiple Appearance Feature Detection.Sensors (Basel, Switzerland) · 2021Article
- Zebrafish automatic monitoring system for conditioning and behavioral analysis.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fish show rapid movements in various behavioral activities or associated with the presence of food. However, in periods of rapid movement, the rate at which occlusion occurs among the fish is quite high, causing inconsistency in the detection and tracking of fish, hindering the fish's identity and behavioral trajectory over a long period of time. Although some algorithms have been proposed to solve these problems, most of their applications were made in groups of fish that swim in shallow water and calm behavior, with few sudden movements. To solve these problems, a convolutional network of object recognition, YOLOv2, was used to delimit the region of the fish heads to optimize individual fish detection. In the tracking phase, the Kalman filter was used to estimate the best state of the fish's head position in each frame and, subsequently, the trajectories of each fish were connected among the frames. The results of the algorithm show adequate performances in the trajectories of groups of zebrafish that exhibited rapid movements.
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