A Systematic Review of Deep Learning Microalgae Classification and Detection-Reference-Cited by-同舟云学术

A Systematic Review of Deep Learning Microalgae Classification and Detection

Published:2023 Issue: Volume:11 Page:57529-57555
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Madkour Dina M.¹^ORCID,Shapiai Mohd Ibrahim¹^ORCID,Mohamad Shaza Eva¹,Aly Hesham Hamdy²,Ismail Zool Hilmi¹^ORCID,Ibrahim Mohd Zamri³^ORCID

Affiliation:

1. Malaysia-Japan International Institute of Technology (MJIIT), Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, Kuala Lumpur, Malaysia

2. Electronics and Communications Engineering Department, Arab Academy for Science, Technology and Maritime Transport, Giza, Egypt

3. Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia

Funder

Universiti Teknologi Malaysia (UTM), UTM Research Management Centre (RMC), and the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme

UTM, UTM RMC to support this study under Research University Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10136693.pdf?arnumber=10136693

Reference75 articles.

1. Water monitoring by means of digital microscopy identification and classification of microalgae

2. Diatom Classification Including Morphological Adaptations Using CNNs

3. Isolation and selection of growth medium for freshwater microalgae Asterarcys quadricellulare for maximum biomass production

4. Deep learning and transfer learning features for plankton classification

5. Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

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