Identification of Cyanobacteria for Harmful Algal Blooms Research Using the YOLO Framework-Reference-Cited by-同舟云学术

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Identification of Cyanobacteria for Harmful Algal Blooms Research Using the YOLO Framework

Published:2023-10-12 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)
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Author:

Li Benjamin¹,Serrano Karen²,Mazzaro Melissa³,Wu Meiyin⁴,Wang Weitian²,Zhu Michelle²

Affiliation:

1. Millburn High School,Millburn,USA

2. Montclair State University,Computer Science Department,Montclair,USA

3. Montclair State University,New Jersey Center for Water Science and Technology,Montclair,USA

4. Montclair State University,Biology Department,Montclair,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10315953/10315721/10316078.pdf?arnumber=10316078

Reference24 articles.

1. Identification and enumeration of cyanobacteria species using a deep neural network

2. Hyperparameter Evolution,2020

3. You only look once: Unified, real-time object detection;redmon;2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2016

4. YOLOv5;jocher,2021

5. Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement

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