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Machine Learning and Deep Learning Based Computational Approaches in Automatic Microorganisms Image Recognition: Methodologies, Challenges, and Developments
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AI
DOI：10.1007/s11831-021-09639-x.png)
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摘要
En 中文
Microorganisms or microbes comprise majority of the diversity on earth and are extremely important to human life. They are also integral to processes in the ecosystem. The process of their recognition is highly tedious, but very much essential in microbiology to carry out different experimentation. To overcome certain challenges, machine learning techniques assist microbiologists in automating the entire process. This paper presents a systematic review of research done using machine learning (ML) and deep leaning techniques in image recognition of different microorganisms. This review investigates certain research questions to analyze the studies concerning image pre-processing, feature extraction, classification techniques, evaluation measures, methodological limitations and technical development over a period of time. In addition to this, this paper also addresses the certain challenges faced by researchers in this field. Total of 100 research publications in the chronological order of their appearance have been considered for the time period 1995-2021. This review will be extremely beneficial to the researchers due to the detailed analysis of different methodologies and comprehensive overview of effectiveness of different ML techniques being applied in microorganism image recognition field.
Keyword:
ARTIFICIAL NEURAL-NETWORKS
MICROSCOPIC IMAGES
CLASSIFICATION
IDENTIFICATION
ALGAE
SEGMENTATION
OBJECT
CNN
IMPROVEMENT
MICROALGAE
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对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
12.1
论文数:
1.8K
被引数:
1.2W
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引用论文
Advances in Chemical and Biological Methods to Identify MicroorganismsFrom Past to Present从过去到现在鉴定微生物的化学和生物学方法的进展.png)
MICROORGANISMSOAAI
MICROORGANISMSIF4.2
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