Applications of artificial neural networks in microorganism image analysis: a comprehensive review from conventional multilayer perceptron to popular convolutional …

J Zhang, C Li, Y Yin, J Zhang, M Grzegorzek - Artificial Intelligence Review, 2023 - Springer
Microorganisms are widely distributed in the human daily living environment. They play an
essential role in environmental pollution control, disease prevention and treatment, and food …

Machine learning and applications in microbiology

SJ Goodswen, JLN Barratt, PJ Kennedy… - FEMS microbiology …, 2021 - academic.oup.com
To understand the intricacies of microorganisms at the molecular level requires making
sense of copious volumes of data such that it may now be humanly impossible to detect …

Machine learning and deep learning based computational approaches in automatic microorganisms image recognition: methodologies, challenges, and …

P Rani, S Kotwal, J Manhas, V Sharma… - … Methods in Engineering, 2022 - Springer
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 …

How can AI help improve food safety?

C Qian, SI Murphy, RH Orsi… - Annual Review of Food …, 2023 - annualreviews.org
With advances in artificial intelligence (AI) technologies, the development and
implementation of digital food systems are becoming increasingly possible. There is …

Meta-album: Multi-domain meta-dataset for few-shot image classification

I Ullah, D Carrión-Ojeda, S Escalera… - Advances in …, 2022 - proceedings.neurips.cc
Abstract We introduce Meta-Album, an image classification meta-dataset designed to
facilitate few-shot learning, transfer learning, meta-learning, among other tasks. It includes …

Detecting semantic anomalies

F Ahmed, A Courville - Proceedings of the AAAI Conference on Artificial …, 2020 - aaai.org
We critically appraise the recent interest in out-of-distribution (OOD) detection and question
the practical relevance of existing benchmarks. While the currently prevalent trend is to …

The gap between theory and practice in function approximation with deep neural networks

B Adcock, N Dexter - SIAM Journal on Mathematics of Data Science, 2021 - SIAM
Deep learning (DL) is transforming whole industries as complicated decision-making
processes are being automated by deep neural networks (DNNs) trained on real-world data …

Deep ensemble model for classification of novel coronavirus in chest X‐ray images

F Ahmad, A Farooq, MU Ghani - Computational intelligence and …, 2021 - Wiley Online Library
The novel coronavirus, SARS‐CoV‐2, can be deadly to people, causing COVID‐19. The
ease of its propagation, coupled with its high capacity for illness and death in infected …

Deep learning for imaging and detection of microorganisms

Y Zhang, H Jiang, T Ye, M Juhas - Trends in Microbiology, 2021 - cell.com
Despite tremendous recent interest, the application of deep learning in microbiology has still
not reached its full potential. To tackle the challenges faced by human-operated microscopy …

Metaverse and microorganism digital twins: A deep transfer learning approach

MB Jamshidi, S Sargolzaei, S Foorginezhad… - Applied Soft …, 2023 - Elsevier
Preparing the infrastructure for analyzing, recognizing, and characterizing microorganisms
in the Metaverse can transform the fields of biology, medicine, and drug discovery …