Results 261 to 270 of about 1,866,820 (291)

FishTrack23: An Ensemble Underwater Dataset for Multi-Object Tracking

IEEE Workshop/Winter Conference on Applications of Computer Vision
Tracking and classifying fish in optical underwater imagery presents several challenges which are encountered less frequently in terrestrial domains.
Matthew Dawkins, Jack H. Prior, Bryon Lewis, Robin Faillettaz, Thompson Banez, Mary Salvi, Audrey Rollo, Julien Simon, Matthew Campbell, Matthew Lucero, Aashish Chaudhary, Benjamin Richards, A. Hoogs   +12 more
semanticscholar   +1 more source

Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset

International Conference on Machine Learning
With the breakthrough of large models, Segment Anything Model (SAM) and its extensions have been attempted to apply in diverse tasks of computer vision.
Shijie Lian, Ziyi Zhang, Hua Li, Wenjie Li, L. T. Yang, Sam Kwong, Runmin Cong   +6 more
semanticscholar   +1 more source

Underwater Acoustic Target Recognition with ResNet18 on ShipsEar Dataset

International Conference on Emerging Technologies, 2021
Underwater Acoustic Target Recognition (UATR) remains one of the most challenging tasks in underwater signal processing due to the lack of labeled data acquisition, the impact of the time-space varying intrinsic characteristics, and the interference from
Feng Hong, Chengwei Liu, Lijuan Guo, Feng Chen, Haihong Feng   +4 more
semanticscholar   +1 more source

Underwater image sharpening and color correction via dataset based on revised underwater image formation model

The Visual Computer
Shunsuke Takao
semanticscholar   +2 more sources

Detection of Underwater Marine Plastic Debris Using an Augmented Low Sample Size Dataset for Machine Vision System: A Deep Transfer Learning Approach

Student Conference on Research and Development, 2021
Waste in aquatic environments devastates aquatic habitats and offers a tall environmental and economical risk. Machine Vision might play a role in resolving this issue by detecting and finally eliminating debris. Using an augmented low sample size from a
Japhet C. Hipolito, Alvin Sarraga Alon, Ryndel V. Amorado, Maricel Grace Z. Fernando, Poul Isaac C. De Chavez   +4 more
semanticscholar   +1 more source

End-To-End Underwater Video Enhancement: Dataset and Model

arXiv.org
Underwater video enhancement (UVE) aims to improve the visibility and frame quality of underwater videos, which has significant implications for marine research and exploration.
Dazhao Du, Enhan Li, Lingyu Si, Fanjiang Xu, Jianwei Niu   +4 more
semanticscholar   +1 more source

ROV6D: 6D Pose Estimation Benchmark Dataset for Underwater Remotely Operated Vehicles

IEEE Robotics and Automation Letters
Accurately localization between multi-robots is crucial for many underwater applications, such as tracking, convoying and subsea intervention tasks. 6D pose estimation is a fundamental task that enables precise object localization in 3D space with full ...
Jingyi Tang, Zeyu Chen, Bowen Fu, Wenjie Lu, Shengquan Li, Xiu Li, Xiangyang Ji   +6 more
semanticscholar   +1 more source

Underwater Detection: A Brief Survey and a New Multitask Dataset

International Journal of Network Dynamics and Intelligence
Article Underwater Detection: A Brief Survey and a New Multitask Dataset Yu Wei 1,2, Yi Wang 1,*, Baofeng Zhu 1, Chi Lin 1, Dan Wu 1, Xinwei Xue 1, and Ruili Wang 3,4 1 School of Software Technology, Dalian University of Technology, Dalian 116620 ...
Yu Wei, Yi Wang, Baofeng Zhu, Chi Lin, Dan Wu, Xinwei Xue, Ruili Wang   +6 more
semanticscholar   +1 more source

S3Simulator: A benchmarking Side Scan Sonar Simulator dataset for Underwater Image Analysis

International Conference on Pattern Recognition
Acoustic sonar imaging systems are widely used for underwater surveillance in both civilian and military sectors. However, acquiring high-quality sonar datasets for training Artificial Intelligence (AI) models confronts challenges such as limited data ...
Kamal Basha, Athira Nambiar
semanticscholar   +1 more source

A dataset to evaluate underwater image restoration methods

OCEANS 2016 - Shanghai, 2016
Image restoration methods have been made to repair images that have some kind of degradation. Most of these methods are designed to deal with the degradation caused by the over-land effects. However, when the images was captured in underwater environments, there are different properties that can degrade the image in unusual ways.
Amanda Duarte, Felipe Codevilla, Joel De O. Gaya, Silvia S. C. Botelho   +3 more
openaire   +1 more source