Results 21 to 30 of about 277,529 (354)

Sharpness evaluation of microscopic detection image for micro parts [PDF]

MATEC Web of Conferences, 2022
According to the characteristics of micro parts microscopic detection image, including the image texture is similar, the edge information is too little and the gray distribution Range is limited, based on the basic principles of algorithm, analyzes the ...
Zhang Xianghui, Yu Zhanjiang, Xu Jinkai, Yu Huadong   +3 more
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An Application of Transfer Learning and Ensemble Learning Techniques for Cervical Histopathology Image Classification

IEEE Access, 2020
In recent years, researches are concentrating on the effectiveness of Transfer Learning (TL) and Ensemble Learning (EL) techniques in cervical histopathology image analysis.
Dan Xue, Xiaomin Zhou, Chen Li, Yudong Yao, Md Mamunur Rahaman, Jinghua Zhang, Hao Chen, Jinpeng Zhang, Shouliang Qi, Hongzan Sun   +9 more
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SEM-RCNN: A Squeeze-and-Excitation-Based Mask Region Convolutional Neural Network for Multi-Class Environmental Microorganism Detection

Applied Sciences, 2022
This paper proposes a novel Squeeze-and-excitation-based Mask Region Convolutional Neural Network (SEM-RCNN) for Environmental Microorganisms (EM) detection tasks.
Jiawei Zhang, Pingli Ma, Tao Jiang, Xin Zhao, Wenjun Tan, Jinghua Zhang, Shuojia Zou, Xinyu Huang, Marcin Grzegorzek, Chen Li   +9 more
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Compressive Image Scanning Microscope

CoRR, 2023
Presented in ...
Ajay Gunalan, Marco Castello, Simonluca Piazza, Shunlei Li, Alberto Diaspro, Leonardo S. Mattos, Paolo Bianchini   +6 more
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A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks

IEEE Access, 2020
Breast cancer is one of the most common and deadliest cancers among women. Since histopathological images contain sufficient phenotypic information, they play an indispensable role in the diagnosis and treatment of breast cancers. To improve the accuracy
Xiaomin Zhou, Chen Li, Md Mamunur Rahaman, Yudong Yao, Shiliang Ai, Changhao Sun, Qian Wang, Yong Zhang, Mo Li, Xiaoyan Li, Tao Jiang, Dan Xue, Shouliang Qi, Yueyang Teng   +13 more
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Bayesian Random Tomography of Particle Systems

Frontiers in Molecular Biosciences, 2021
Random tomography is a common problem in imaging science and refers to the task of reconstructing a three-dimensional volume from two-dimensional projection images acquired in unknown random directions. We present a Bayesian approach to random tomography.
Nima Vakili, Michael Habeck, Michael Habeck   +2 more
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Microscopic Live Electrooptic Imaging [PDF]

Scientific Reports, 2017
AbstractLive electrooptic imaging (LEI) in the microscopic range has been successfully demonstrated for the first time. The finest resolution achieved in the present study is 2.7 μm, which is finer than the previous record by more than an order of magnitude.
Masahiro Tsuchiya, Shinji Fukui, Muneo Yorinaga   +2 more
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A comparative study of gastric histopathology sub-size image classification: From linear regression to visual transformer

Frontiers in Medicine, 2022
IntroductionGastric cancer is the fifth most common cancer in the world. At the same time, it is also the fourth most deadly cancer. Early detection of cancer exists as a guide for the treatment of gastric cancer.
Weiming Hu, Haoyuan Chen, Wanli Liu, Xiaoyan Li, Hongzan Sun, Xinyu Huang, Marcin Grzegorzek, Marcin Grzegorzek, Chen Li   +8 more
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Impact of Experimental Conditions on Extracellular Vesicles’ Proteome: A Comparative Study

Life, 2023
Extracellular vesicle (EV) research is a rapidly developing field, mainly due to the key role of EVs in intercellular communication and pathophysiological processes.
Tímea Böröczky, Gabriella Dobra, Mátyás Bukva, Edina Gyukity-Sebestyén, Éva Hunyadi-Gulyás, Zsuzsanna Darula, Péter Horváth, Krisztina Buzás, Mária Harmati   +8 more
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An Application of Pixel Interval Down-Sampling (PID) for Dense Tiny Microorganism Counting on Environmental Microorganism Images

Applied Sciences, 2022
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 convolutional neural network (CNN) model with an encoder–decoder architecture.
Jiawei Zhang, Xin Zhao, Tao Jiang, Md Mamunur Rahaman, Yudong Yao, Yu-Hao Lin, Jinghua Zhang, Ao Pan, Marcin Grzegorzek, Chen Li   +9 more
doaj   +1 more source