[HTML][HTML] Applications of deep learning in fish habitat monitoring: A tutorial and survey
Marine ecosystems and their fish habitats are becoming increasingly important due to their
integral role in providing a valuable food source and conservation outcomes. Due to their …
integral role in providing a valuable food source and conservation outcomes. Due to their …
Research challenges, recent advances, and popular datasets in deep learning-based underwater marine object detection: A review
Underwater marine object detection, as one of the most fundamental techniques in the
community of marine science and engineering, has been shown to exhibit tremendous …
community of marine science and engineering, has been shown to exhibit tremendous …
Lightweight deep neural network for joint learning of underwater object detection and color conversion
Underwater image processing has been shown to exhibit significant potential for exploring
underwater environments. It has been applied to a wide variety of fields, such as underwater …
underwater environments. It has been applied to a wide variety of fields, such as underwater …
A realistic fish-habitat dataset to evaluate algorithms for underwater visual analysis
Visual analysis of complex fish habitats is an important step towards sustainable fisheries for
human consumption and environmental protection. Deep Learning methods have shown …
human consumption and environmental protection. Deep Learning methods have shown …
Overview of lifeclef 2024: Challenges on species distribution prediction and identification
Biodiversity monitoring using machine learning and AI-based approaches is becoming
increasingly popular. It allows for providing detailed information on species distribution and …
increasingly popular. It allows for providing detailed information on species distribution and …
Detection of marine animals in a new underwater dataset with varying visibility
M Pedersen, J Bruslund Haurum… - Proceedings of the …, 2019 - openaccess.thecvf.com
The increasing demand for marine monitoring calls for robust automated systems to support
researchers in gathering information from marine ecosystems. This includes computer vision …
researchers in gathering information from marine ecosystems. This includes computer vision …
Overview of lifeclef 2022: an evaluation of machine-learning based species identification and species distribution prediction
Building accurate knowledge of the identity, the geographic distribution and the evolution of
species is essential for the sustainable development of humanity, as well as for biodiversity …
species is essential for the sustainable development of humanity, as well as for biodiversity …
Domain‐specific neural networks improve automated bird sound recognition already with small amount of local data
P Lauha, P Somervuo, P Lehikoinen… - Methods in Ecology …, 2022 - Wiley Online Library
An automatic bird sound recognition system is a useful tool for collecting data of different
bird species for ecological analysis. Together with autonomous recording units (ARUs), such …
bird species for ecological analysis. Together with autonomous recording units (ARUs), such …
Deep learning-based visual recognition of rumex for robotic precision farming
In this paper we address the problem of recognising the Broad-leaved dock (Rumex
obtusifolius L.) in grasslands from high-resolution 2D images. We discuss and present the …
obtusifolius L.) in grasslands from high-resolution 2D images. We discuss and present the …
Application of deep learning-based object detection techniques in fish aquaculture: a review
H Liu, X Ma, Y Yu, L Wang, L Hao - Journal of Marine Science and …, 2023 - mdpi.com
Automated monitoring and analysis of fish's growth status and behaviors can help scientific
aquaculture management and reduce severe losses due to diseases or overfeeding. With …
aquaculture management and reduce severe losses due to diseases or overfeeding. With …