Run the command (linux) to evaluate map for a YOLO-Fish models. A robust fish detection model for real-time underwater fish detection in any marine environments.

Dec 1, 2022 · In this paper, we propose YOLO-Fish, a deep learning based fish detection model. We have proposed two models, YOLO-Fish-1 and YOLO-Fish-2. YOLO-Fish-1 enhances YOLOv3 by fixing the issue of upsampling step sizes of to reduce the misdetection of tiny fish.

This repository implements YOLOv3 and DeepSORT for tracking and counting of 2 different fish species in an aquarium. YOLO (You only look once) uses CNN to detect objects in real time.

Sep 23, 2024 · To summarize, we introduced the FishDet-YOLO algorithm to address the challenges posed by the complexity of underwater environments and the diversity of fish species, with the aim of enhancing both the accuracy and efficiency of underwater fish detection.

In our investigation of effective fish detection within underwater environments, we employed two state-of-the-art deep learning models, namely YOLO v7 and YOLO v8 , which are known for their remarkable performance in object detection tasks.

This project focuses on the detection and tracking of fish in images using the YOLO (You Only Look Once) object detection model. The primary goal is to identify fish in various images, annotate them with bounding boxes, and understand their movement patterns.

Jan 3, 2021 · In this paper, we provide a fish farm monitoring system that is based on a combination of algorithms to detect fish count and trajectories. Firstly, we enhance turbid underwater images by Multi-scale Retinex algorithm (Petro et al. 2014) which makes it …

Feb 20, 2025 · YOLO-Fish-1 modifies YOLOv3 by adjusting the upsampling process to improve detection of small fish, while YOLO-Fish-2 adds Spatial Pyramid Pooling to handle dynamic and complex environments.

Jul 9, 2024 · The YOLO-Fish model is one of the most famous models in this field, and it is specially designed to detect fish in realistic underwater environments. The model uses sophisticated algorithms to address the challenges posed by underwater conditions, proposing a robust method of fish detection.

Dec 1, 2022 · In this paper, we propose YOLO-Fish, a deep learning based fish detection model. We have proposed two models, YOLO-Fish-1 and YOLO-Fish-2. YOLO-Fish-1 enhances YOLOv3 by fixing the issue of upsampling step sizes of to reduce the misdetection of tiny fish.