Cell Detection

46 papers with code • 4 benchmarks • 4 datasets

Cell Detection

Most implemented papers

On Complex Valued Convolutional Neural Networks

Recognito-Vision/NIST-FRVT-Top-1-Face-Recognition 29 Feb 2016

The resulting model is shown to be a restricted form of a real valued CNN with twice the parameters.

Cell Detection in Microscopy Images with Deep Convolutional Neural Network and Compressed Sensing

yaoxuexa/CNNCS 10 Aug 2017

In this paper, we seek a different route and propose a convolutional neural network (CNN)-based cell detection method that uses encoding of the output pixel space.

Cell Detection with Star-convex Polygons

stardist/stardist 9 Jun 2018

Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications.

Contour Proposal Networks for Biomedical Instance Segmentation

FZJ-INM1-BDA/celldetection 7 Apr 2021

We construct CPN models with different backbone networks, and apply them to instance segmentation of cells in datasets from different modalities.

TABBIE: Pretrained Representations of Tabular Data

SFIG611/tabbie NAACL 2021

Existing work on tabular representation learning jointly models tables and associated text using self-supervised objective functions derived from pretrained language models such as BERT.

Cell Detection in Domain Shift Problem Using Pseudo-Cell-Position Heatmap

hyeonwoocho7/Cell_Detection-MICCAI 19 Jul 2021

We propose an unsupervised domain adaptation method for cell detection using the pseudo-cell-position heatmap, where a cell centroid becomes a peak with a Gaussian distribution in the map.

Multi-Class Cell Detection Using Spatial Context Representation

topoxlab/mcspatnet ICCV 2021

In digital pathology, both detection and classification of cells are important for automatic diagnostic and prognostic tasks.

A Pragmatic Machine Learning Approach to Quantify Tumor Infiltrating Lymphocytes in Whole Slide Images

uit-hdl/histology 14 Feb 2022

Our approach is to transfer an open source machine learning method for segmentation and classification of nuclei in H&E slides trained on public data to TIL quantification without manual labeling of our data.

Self-supervised pseudo-colorizing of masked cells

roydenwa/cell-centroid-former 12 Feb 2023

Self-supervised learning, which is strikingly referred to as the dark matter of intelligence, is gaining more attention in biomedical applications of deep learning.