Coral Detection in fluorescence images and videos using YOLOV3 and YOLOV5-Reference-Cited by-同舟云学术

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Coral Detection in fluorescence images and videos using YOLOV3 and YOLOV5

Published:2023-03-07 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Business Analytics for Technology and Security (ICBATS)
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Author:

Gorro Ken¹,Ilano Anthony¹,Ranolo Elmo¹,Pineda Hedeliza¹,Sintos Cristine¹,Gorro Apple Jane¹

Affiliation:

1. Cebu Technological University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10111090/10111095/10111194.pdf?arnumber=10111194

Reference23 articles.

1. Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model

2. Classification of morphologically similar algae and cyanobacteria using Mueller matrix imaging and convolutional neural networks

3. A Low-Cost Automated Digital Microscopy Platform for Automatic Identification of Diatoms

4. Microalgae Detection Using a Deep Learning Object Detection Algorithm, YOLOv3;park;J Korean Soc Water Environ,2021

5. Multi-Target Deep Learning for Algal Detection and Classification

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1. Image Detection of Seaweed, Seagrass, and Coral in Coastal and Underwater Marine Ecosystems;2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA);2023-11-14

2. Seagrass Blurred Image Enhancement and Detection using YOLO and CLAHE Algorithms Performance Comparison;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20

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