220 citations · 286 across the 16 of their papers we have counts for
12 papers · 1 filter
CVM-Cervix: A Hybrid Cervical Pap-Smear Image Classification Framework Using CNN, Visual Transformer and Multilayer Perceptron
Wanli Liu, Chen Li, Ning Xu +9
Cervical cancer is the seventh most common cancer among all the cancers worldwide and the fourth most common cancer among women. Cervical cytopathology image classification is an i…
An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism images
Jiawei Zhang, Xin Zhao, Tao Jiang +7
This paper proposes a novel pixel interval down-sampling network (PID-Net) for dense tiny object (yeast cells) counting tasks with higher accuracy. The PID-Net is an end-to-end con…
A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements
Jiawei Zhang, Chen Li, Md Mamunur Rahaman +6
With the acceleration of urbanization and living standards, microorganisms play increasingly important roles in industrial production, bio-technique, and food safety testing. Micro…
EMDS-6: Environmental Microorganism Image Dataset Sixth Version for Image Denoising, Segmentation, Feature Extraction, Classification and Detection Methods Evaluation
Peng Zhao, Chen Li, Md Mamunur Rahaman +7
Environmental microorganisms (EMs) are ubiquitous around us and have an important impact on the survival and development of human society. However, the high standards and strict re…
EMDS-7: Environmental Microorganism Image Dataset Seventh Version for Multiple Object Detection Evaluation
Hechen Yang, Chen Li, Xin Zhao +10
The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) is a microscopic image data set, including the original Environmental Microorganism images (EMs) and the corr…
A Comparison for Patch-level Classification of Deep Learning Methods on Transparent Environmental Microorganism Images: from Convolutional Neural Networks to Visual Transformers
Hechen Yang, Chen Li, Jinghua Zhang +5
Nowadays, analysis of Transparent Environmental Microorganism Images (T-EM images) in the field of computer vision has gradually become a new and interesting spot. This paper compa…
A Comparative Study of Deep Learning Classification Methods on a Small Environmental Microorganism Image Dataset (EMDS-6): from Convolutional Neural Networks to Visual Transformers
Peng Zhao, Chen Li, Md Mamunur Rahaman +5
In recent years, deep learning has made brilliant achievements in Environmental Microorganism (EM) image classification. However, image classification of small EM datasets has stil…
Is the aspect ratio of cells important in deep learning? A robust comparison of deep learning methods for multi-scale cytopathology cell image classification: from convolutional neural networks to visual transformers
Wanli Liu, Chen Li, Md Mamunur Rahamana +8
Cervical cancer is a very common and fatal type of cancer in women. Cytopathology images are often used to screen for this cancer. Given that there is a possibility that many error…
A New Pairwise Deep Learning Feature For Environmental Microorganism Image Analysis
Frank Kulwa, Chen Li, Jinghua Zhang +6
Environmental microorganism (EM) offers a high-efficient, harmless, and low-cost solution to environmental pollution. They are used in sanitation, monitoring, and decomposition of…
EMDS-5: Environmental Microorganism Image Dataset Fifth Version for Multiple Image Analysis Tasks
Zihan Li, Chen Li, Yudong Yao +7
Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (…
A Hierarchical Conditional Random Field-based Attention Mechanism Approach for Gastric Histopathology Image Classification
Yixin Li, Xinran Wu, Chen Li +7
In the Gastric Histopathology Image Classification (GHIC) tasks, which are usually weakly supervised learning missions, there is inevitably redundant information in the images. The…
A Multi-scale CNN-CRF Framework for Environmental Microorganism Image Segmentation
Jinghua Zhang, Chen Li, Frank Kulwa +6
To assist researchers to identify Environmental Microorganisms (EMs) effectively, a Multiscale CNN-CRF (MSCC) framework for the EM image segmentation is proposed in this paper. The…