Fish Detection
2 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Fish Detection
DeepFish
Fishnet Open Images
Latest papers with no code
FishNet: A Large-scale Dataset and Benchmark for Fish Recognition, Detection, and Functional Trait Prediction
Aquatic species are essential components of the world's ecosystem, and the preservation of aquatic biodiversity is crucial for maintaining proper ecosystem functioning.
Utility-Oriented Underwater Image Quality Assessment Based on Transfer Learning
Based on this task, we build an Underwater Image Utility Database (UIUD) and a learning-based Underwater Image Utility Measure (UIUM).
Fake Hilsa Fish Detection Using Machine Vision
In this research, we have proposed a method that can readily identify original Hilsa fish and fake Hilsa fish.
A deep neural network for multi-species fish detection using multiple acoustic cameras
1 However the results point a new solution for dealing with complex data, such as sonar data, which can also be reapplied in other cases where the signal-to-noise ratio is a challenge.
The Fishnet Open Images Database: A Dataset for Fish Detection and Fine-Grained Categorization in Fisheries
To address this, we present the Fishnet Open Images Database, a large dataset of EM imagery for fish detection and fine-grained categorization onboard commercial fishing vessels.
Temperate Fish Detection and Classification: a Deep Learning based Approach
In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering.
Fish Detection Using Deep Learning
An advanced system with more computing power can facilitate deep learning feature, which exploit many neural network algorithms to simulate human brains.
Underwater Fish Detection with Weak Multi-Domain Supervision
Given a sufficiently large training dataset, it is relatively easy to train a modern convolution neural network (CNN) as a required image classifier.
Assessing fish abundance from underwater video using deep neural networks
Uses of underwater videos to assess diversity and abundance of fish are being rapidly adopted by marine biologists.
