Results 11 to 20 of about 4,817,492 (231)

Underwater Camouflage Object Detection Dataset

open access: yesCoRR, 2023
We have made a dataset of camouflage object detection mainly for complex seabed scenes, and named it UnderWater RGB&Sonar,or UW-RS for short. The UW-RS dataset contains a total of 1972 image data. The dataset mainly consists of two parts, namely underwater optical data part (UW-R dataset) and underwater sonar data part (UW-S dataset).
Feng Dong, Jinchao Zhu
openaire   +3 more sources

A Comparison of Deep Learning Approach for Underwater Object Detection [PDF]

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022
In recent years, marine ecosystems and fisheries have become potential resources. Therefore, monitoring these objects will be essential to ensure their existence.
Nurcahyani Wulandari   +2 more
doaj   +2 more sources

Excavating RoI Attention for Underwater Object Detection

open access: yes2022 IEEE International Conference on Image Processing (ICIP), 2022
Self-attention is one of the most successful designs in deep learning, which calculates the similarity of different tokens and reconstructs the feature based on the attention matrix. Originally designed for NLP, self-attention is also popular in computer vision, and can be categorized into pixel-level attention and patch-level attention.
Xutao Liang, Pinhao Song
openaire   +4 more sources

Polarization-Enhanced Multi-Target Underwater Salient Object Detection

open access: yesPhotonics
Salient object detection (SOD) plays a critical role in underwater exploration systems. Traditional SOD approaches encounter notable constraints in underwater image analysis, primarily stemming from light scattering and absorption effects induced by ...
Jiayi Song   +5 more
doaj   +2 more sources

Refining features for underwater object detection at the frequency level [PDF]

open access: yesFrontiers in Marine Science
In recent years, underwater object detection (UOD) has become a prominent research area in the computer vision community. However, existing UOD approaches are still vulnerable to underwater environments, which mainly include light scattering and color ...
Wenling Wang   +3 more
doaj   +2 more sources

An Improved YOLOv9s Algorithm for Underwater Object Detection

open access: yesJournal of Marine Science and Engineering
Monitoring marine life through underwater object detection technology serves as a primary means of understanding biodiversity and ecosystem health. However, the complex marine environment, poor resolution, color distortion in underwater optical imaging ...
Shize Zhou   +5 more
doaj   +2 more sources

EF-UODA: Underwater Object Detection Based on Enhanced Feature

open access: yesJournal of Marine Science and Engineering
The ability to detect underwater objects accurately is important in marine environmental engineering. Although many kinds of underwater object detection algorithms with relatively high accuracy have been proposed, they involve a large number of ...
Yunqin Zu   +4 more
doaj   +2 more sources

UICE-MIRNet guided image enhancement for underwater object detection

open access: yesScientific Reports
Underwater object detection is a crucial aspect of monitoring the aquaculture resources to preserve the marine ecosystem. In most cases, Low-light and scattered lighting conditions create challenges for computer vision-based underwater object detection ...
Pratima Sarkar   +3 more
doaj   +2 more sources

Underwater object detection algorithm based on channel attention and feature fusion

open access: yesXibei Gongye Daxue Xuebao, 2022
Due to the color deviation, low contrast and fuzzy object in underwater optical images, there are some problems in underwater object detection, such as missed detection and false detection.
ZHANG Yan   +3 more
doaj   +1 more source

A Dataset and Benchmark of Underwater Object Detection for Robot Picking [PDF]

open access: yes2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021
Underwater object detection for robot picking has attracted a lot of interest. However, it is still an unsolved problem due to several challenges. We take steps towards making it more realistic by addressing the following challenges. Firstly, the currently available datasets basically lack the test set annotations, causing researchers must compare ...
Chongwei Liu   +6 more
openaire   +2 more sources

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