Papers with Code 아카이브

Cell Detection

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AMiiR-S/Inceptnet_cancer_recognition

공식 코드

INCEPTNET: Precise And Early Disease Detection Application For Medical Images Analyses

https://github.com/Ale9806/eVLLM

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μ-Bench: A Vision-Language Benchmark for Microscopy Understanding

https://github.com/Chrisa142857/PolarNet-GCdet

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Cervical Glandular Cell Detection from Whole Slide Image with Out-Of-Distribution Data

https://github.com/ChristianMarzahl/EIPH_WSI

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Inter-Species Cell Detection: Datasets on pulmonary hemosiderophages in equine, human and feline specimens

https://github.com/ChristophReich1996/Cell-DETR

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Attention-Based Transformers for Instance Segmentation of Cells in Microstructures

https://github.com/FZJ-INM1-BDA/celldetection

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Contour Proposal Networks for Biomedical Instance Segmentation

https://github.com/FujiiKazuma/CDFIAPLSUP

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Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification

https://github.com/Khayrulbuet13/LymphoML

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Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning

https://github.com/LucasKirsten/Deep-Cell-Tracking-EBB

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Cell Tracking-by-detection using Elliptical Bounding Boxes

https://github.com/MIDA-group/Cell-Detection

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A Comparison of Deep Learning Methods for Cell Detection in Digital Cytology

https://github.com/SFIG611/tabbie

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TABBIE: Pretrained Representations of Tabular Data

https://github.com/SHIDCenter/PathoNet

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PathoNet: Deep learning assisted evaluation of Ki-67 and tumor infiltrating lymphocytes (TILs) as prognostic factors in breast cancer; A large dataset and baseline

https://github.com/SaadUllahAkram/CellTracker

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Cell Tracking via Proposal Generation and Selection

https://github.com/YemanBrhane/AwareNet

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Cell abundance aware deep learning for cell detection on highly imbalanced pathological data

https://github.com/catchxu/acsleuth

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Domain Adaptive and Fine-grained Anomaly Detection for Single-cell Sequencing Data and Beyond

https://github.com/cmb-chula/recasnet

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ReCasNet: Improving consistency within the two-stage mitosis detection framework

https://github.com/cosmoiknoslab/nulite

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NuLite -- Lightweight and Fast Model for Nuclei Instance Segmentation and Classification

https://github.com/cpystan/psm

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Exploring Unsupervised Cell Recognition with Prior Self-activation Maps

https://github.com/cviu-csu/cr4cacd

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Exploring Contextual Relationships for Cervical Abnormal Cell Detection

https://github.com/dair-iitd/degpr

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DeGPR: Deep Guided Posterior Regularization for Multi-Class Cell Detection and Counting

https://github.com/hula-ai/DAMA

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Multiplexed Immunofluorescence Brain Image Analysis Using Self-Supervised Dual-Loss Adaptive Masked Autoencoder

https://github.com/hyeonwoocho7/Cell_Detection-MICCAI

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

https://github.com/hyeonwoocho7/UDA-Cell-Detection

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Effective Pseudo-Labeling based on Heatmap for Unsupervised Domain Adaptation in Cell Detection

https://github.com/joey-qi/saic

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Style-Aligned Image Composition for Robust Detection of Abnormal Cells in Cytopathology

https://github.com/joeybyc/cell_detection

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Advancing Cell Detection in Anterior Segment Optical Coherence Tomography Images

https://github.com/jwhgdeu/tsbp

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TSBP: Improving Object Detection in Histology Images via Test-time Self-guided Bounding-box Propagation

https://github.com/kaczmarj/champkit

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Evaluating histopathology transfer learning with ChampKit

https://github.com/lely475/ocelot23algo

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SoftCTM: Cell detection by soft instance segmentation and consideration of cell-tissue interaction

https://github.com/lisaweijler/fate

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FATE: Feature-Agnostic Transformer-based Encoder for learning generalized embedding spaces in flow cytometry data

https://github.com/melon-xu/topocellgen

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TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model

https://github.com/mkang315/CST-YOLO

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CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer

https://github.com/naivete5656/SCDTC

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Semi-supervised Cell Detection in Time-lapse Images Using Temporal Consistency

https://github.com/naivete5656/WSCTBFP

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Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation

https://github.com/namtuanly/MTL-TabNet

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An End-to-End Multi-Task Learning Model for Image-based Table Recognition

https://github.com/poldap/SpotNet

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SpotNet - Learned iterations for cell detection in image-based immunoassays

https://github.com/quinngroup/3Dcell_tracking_DSAA2019

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Lightweight and Scalable Particle Tracking and Motion Clustering of 3D Cell Trajectories

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.