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U-Net: deep learning for cell counting, detection, and morphometry | Nature Methods
U-Net: deep learning for cell counting, detection, and morphometry | Nature Methods

Applied Sciences | Free Full-Text | Deep Learning and Transfer Learning for Automatic Cell Counting in Microscope Images of Human Cancer Cell Lines
Applied Sciences | Free Full-Text | Deep Learning and Transfer Learning for Automatic Cell Counting in Microscope Images of Human Cancer Cell Lines

An Automated Blood Cells Counting and Classification Framework using Mask R-CNN Deep Learning Model | Semantic Scholar
An Automated Blood Cells Counting and Classification Framework using Mask R-CNN Deep Learning Model | Semantic Scholar

TruAI Based on Deep-Learning Technology for Robust, Label-Free Nucleus Detection and Segmentation in Microwell Plates | Olympus LS
TruAI Based on Deep-Learning Technology for Robust, Label-Free Nucleus Detection and Segmentation in Microwell Plates | Olympus LS

Microscopy Cell Counting with Fully Convolutional Regression Networks
Microscopy Cell Counting with Fully Convolutional Regression Networks

Example results of three deep-learning detection-based cell counting... | Download Scientific Diagram
Example results of three deep-learning detection-based cell counting... | Download Scientific Diagram

Development of deep learning-based method for counting of tyrosine... | Download Scientific Diagram
Development of deep learning-based method for counting of tyrosine... | Download Scientific Diagram

GitHub - MahmudulAlam/Automatic-Identification-and-Counting-of-Blood-Cells: A machine learning approach of automatic identification and counting of blood cells (RBC, WBC, and Platelet) with KNN and IOU based verification.
GitHub - MahmudulAlam/Automatic-Identification-and-Counting-of-Blood-Cells: A machine learning approach of automatic identification and counting of blood cells (RBC, WBC, and Platelet) with KNN and IOU based verification.

Accurate and reliable cell counting using holographic microscopy and machine learning algorithms - - In this study, we evaluated the performance of a cell counter according to the CLSI EP05-A32.
Accurate and reliable cell counting using holographic microscopy and machine learning algorithms - - In this study, we evaluated the performance of a cell counter according to the CLSI EP05-A32.

Machine learning approach of automatic identification and counting of blood cells - Alam - 2019 - Healthcare Technology Letters - Wiley Online Library
Machine learning approach of automatic identification and counting of blood cells - Alam - 2019 - Healthcare Technology Letters - Wiley Online Library

Real-time cell counting in microscopy images using Neural Networks | by Dmitry Urukov | Analytics Vidhya | Medium
Real-time cell counting in microscopy images using Neural Networks | by Dmitry Urukov | Analytics Vidhya | Medium

Sensors | Free Full-Text | Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting
Sensors | Free Full-Text | Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

Cell-counting on the VGG dataset We demonstrate the versatility of UDCT... | Download Scientific Diagram
Cell-counting on the VGG dataset We demonstrate the versatility of UDCT... | Download Scientific Diagram

Machine Learning Radically Reduces Workload of Cell Counting for Disease Diagnosis - Hematology - Labmedica.com
Machine Learning Radically Reduces Workload of Cell Counting for Disease Diagnosis - Hematology - Labmedica.com

NuSeT: A deep learning tool for reliably separating and analyzing crowded cells | PLOS Computational Biology
NuSeT: A deep learning tool for reliably separating and analyzing crowded cells | PLOS Computational Biology

U-Net Deep-Learning-Based 3D Cell Counter for the Quality Control of 3D Cell-Based Assays through Seed Cell Measurement - Eun Ji Jeong, Donghyuk Choi, Dong Woo Lee, 2021
U-Net Deep-Learning-Based 3D Cell Counter for the Quality Control of 3D Cell-Based Assays through Seed Cell Measurement - Eun Ji Jeong, Donghyuk Choi, Dong Woo Lee, 2021

Real-time cell counting in microscopy images using Neural Networks | by Dmitry Urukov | Analytics Vidhya | Medium
Real-time cell counting in microscopy images using Neural Networks | by Dmitry Urukov | Analytics Vidhya | Medium

Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos with Bidirectional Temporal Deep Learning Tracking Algorithm | DeepAI
Automated Blood Cell Counting from Non-invasive Capillaroscopy Videos with Bidirectional Temporal Deep Learning Tracking Algorithm | DeepAI

A deep learning algorithm for 3D cell detection in whole mouse brain image datasets | PLOS Computational Biology
A deep learning algorithm for 3D cell detection in whole mouse brain image datasets | PLOS Computational Biology

PDF] Machine learning approach of automatic identification and counting of blood cells | Semantic Scholar
PDF] Machine learning approach of automatic identification and counting of blood cells | Semantic Scholar

Machine learning-based automated yeast cell counting under a complicated background with ilastik and ImageJ - Authorea
Machine learning-based automated yeast cell counting under a complicated background with ilastik and ImageJ - Authorea

Deep learning-based image processing in optical microscopy | SpringerLink
Deep learning-based image processing in optical microscopy | SpringerLink

Cell Counting and Segmentation of Immunohistochemical Images in the Spinal Cord: Comparing Deep Learning and Traditional Approaches | Semantic Scholar
Cell Counting and Segmentation of Immunohistochemical Images in the Spinal Cord: Comparing Deep Learning and Traditional Approaches | Semantic Scholar