Deep learning‐based single‐cell optical image studies
Optical imaging technology that has the advantages of high sensitivity and cost‐
effectiveness greatly promotes the progress of nondestructive single‐cell studies. Complex …
effectiveness greatly promotes the progress of nondestructive single‐cell studies. Complex …
Deep learning based HEp-2 image classification: A comprehensive review
Classification of HEp-2 cell patterns plays a significant role in the indirect
immunofluorescence test for identifying autoimmune diseases in the human body. Many …
immunofluorescence test for identifying autoimmune diseases in the human body. Many …
River ice segmentation with deep learning
This article deals with the problem of computing surface concentrations for two types of river
ice from digital images acquired during freeze-up. It presents the results of attempting to …
ice from digital images acquired during freeze-up. It presents the results of attempting to …
Deep learning based microscopic cell images classification framework using multi-level ensemble
Background and objectives Advancement of the ultra-fast microscopic images acquisition
and generation techniques give rise to the automated artificial intelligence (AI)-based …
and generation techniques give rise to the automated artificial intelligence (AI)-based …
Efficiently recognition of vaginal micro-ecological environment based on Convolutional Neural Network
Vaginal diseases caused by vaginal micro-ecological abnormalities mainly include
Vulvovaginal Candidiasis (VVC), Aerobic Vaginitis (AV), and Bacterial Vaginosis (BV) …
Vulvovaginal Candidiasis (VVC), Aerobic Vaginitis (AV), and Bacterial Vaginosis (BV) …
Combined Data Augmentation for HEp-2 Cells Image Classification
Abstract The Antinuclear Antibody (ANA) test is a valuable diagnostic tool for autoimmune
disorders that uses Indirect Immunofluorescence (IIF) microscopy with HEp-2 cells as the …
disorders that uses Indirect Immunofluorescence (IIF) microscopy with HEp-2 cells as the …
Algorithm for Crop Pest and Disease Recognition Based on Residual Network
J Feng, X Chen, D Fu, Q Liu - 2023 5th International Academic …, 2023 - ieeexplore.ieee.org
Considering the current mainstream convolutional neural network depth is now deeper and
problems like many parameters, network degradation. This paper proposes a plant pest and …
problems like many parameters, network degradation. This paper proposes a plant pest and …
A HEp-2 Cell Image Classification Model Based on Deep Residual Shrinkage Network Combined with Dilated Convolution
C Wang, T He, J Liu, D Li, Y Wen - International Conference on Intelligent …, 2022 - Springer
Detection of antinuclear antibodies (ANA) in human epithelial cells (HEp-2) is a common
method for the diagnosis of autoimmune diseases. The recognition of fluorescence images …
method for the diagnosis of autoimmune diseases. The recognition of fluorescence images …
Check for A HEp-2 Cell Image Classification Model Based on Deep Residual Shrinkage Network Combined with Dilated Convolution Chen Wang1, 2 (), Tao He² …
C Wang, T He, J Liu, D Li - … Processing XI: 12th IFIP TC 12 …, 2022 - books.google.com
Detection of antinuclear antibodies (ANA) in human epithelial cells (HEp-2) is a common
method for the diagnosis of autoimmune diseases. The recognition of fluorescence images …
method for the diagnosis of autoimmune diseases. The recognition of fluorescence images …
Deep Learning Based Heat Sealing Quality Inspection
L Wanqing, Z Qinghua, Z Xiaowei - 2021 9th International …, 2021 - ieeexplore.ieee.org
In order to ensure the tightness of the heat-sealing of pharmaceutical packaging, a method
of tightness detection based on image processing and deep learning is proposed. The bit …
of tightness detection based on image processing and deep learning is proposed. The bit …