Bibliographic Details
| Title: |
DePondFi’23 Challenge on Real-Time Pond Environment: Methods and Results |
| Authors: |
A. Sasithradevi, R. Suganya, P. Prakash, S. Mohamed Mansoor Roomi, M. Vijayalakshmi, Sabari Nathan, P. Kasthuri, J. Persiya, L. Brighty Ebenezer, Sparsh Jain, Sshubam Verma, S. Balasubramanian, M. Sai Subramaniam, T. Sai Sriram, M. Pranav Phanindra Sai, Chandan Raj, Amandeep Yadav, Ritik Payak, Suman Paul Choudhury, Rohit Singh |
| Source: |
IEEE Access, Vol 12, Pp 157975-157987 (2024) |
| Publisher Information: |
IEEE, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Electrical engineering. Electronics. Nuclear engineering |
| Subject Terms: |
Aquaculture, underwater challenges, detection models, mAP, computational time, Electrical engineering. Electronics. Nuclear engineering, TK1-9971 |
| More Details: |
This article summarizes the Detection of Pond Fish Challenge (DePondfi’23 Challenge), held during the National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2023). The main goal of the challenge was to find the most effective methods for detecting pond fish in underwater images, overcoming obstacles such as poor visibility, variations in turbidity, and environmental shifts. Sixty participants registered, with 15 teams submitting results for phase 1. The challenge concluded with four teams earning top honors based on mAP (mean Average Precision) score and time complexity. The mAP scores achieved by toppers are as follows: DETECTRON - 38.93%, DMACS SAI - 36.65%, PondVision - 31.63%, and Sahajeevis - 29.06%. This article describes the toppers method and discusses the detection results. Our challenge event is in line with Sustainable Development Goal 14, which focuses on the conservation and sustainable utilization of ponds and marine resources for sustainable development. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2169-3536 |
| Relation: |
https://ieeexplore.ieee.org/document/10720772/; https://doaj.org/toc/2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3482867 |
| Access URL: |
https://doaj.org/article/b0cac41aab52458ab51f8090e4b34e91 |
| Accession Number: |
edsdoj.b0cac41aab52458ab51f8090e4b34e91 |
| Database: |
Directory of Open Access Journals |
