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Applications of artificial neural networks in microorganism image analysis: a comprehensive review from conventional multilayer perceptron to popular convolutional …
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 …
essential role in environmental pollution control, disease prevention and treatment, and food …
Machine learning and applications in microbiology
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 …
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 …
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 …
important to human life. They are also integral to processes in the ecosystem. The process of …
How can AI help improve food safety?
With advances in artificial intelligence (AI) technologies, the development and
implementation of digital food systems are becoming increasingly possible. There is …
implementation of digital food systems are becoming increasingly possible. There is …
Meta-album: Multi-domain meta-dataset for few-shot image classification
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 …
facilitate few-shot learning, transfer learning, meta-learning, among other tasks. It includes …
Detecting semantic anomalies
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 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
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 …
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
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 …
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 …
not reached its full potential. To tackle the challenges faced by human-operated microscopy …
Metaverse and microorganism digital twins: A deep transfer learning approach
Preparing the infrastructure for analyzing, recognizing, and characterizing microorganisms
in the Metaverse can transform the fields of biology, medicine, and drug discovery …
in the Metaverse can transform the fields of biology, medicine, and drug discovery …