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Histopathological Image Classification
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Histopathological Image Classification with Cell Morphology Aware Deep Neural Networks
Supervised Contrastive Vision Transformer for Breast Histopathological Image Classification
Focused Active Learning for Histopathological Image Classification
A Novel Approach to Breast Cancer Histopathological Image Classification Using Cross-Colour Space Feature Fusion and Quantum-Classical Stack Ensemble Method
CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification
Automatic Report Generation for Histopathology images using pre-trained Vision Transformers and BERT
Histopathological Image Classification and Vulnerability Analysis using Federated Learning
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification
SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology Image
Breast Cancer Detection and Diagnosis: A comparative study of state-of-the-arts deep learning architectures
Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization
Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak Labels
IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach
DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain Medical Images
Application of Graph Based Features in Computer Aided Diagnosis for Histopathological Image Classification of Gastric Cancer
Self-distillation Augmented Masked Autoencoders for Histopathological Image Classification
ScoreNet: Learning Non-Uniform Attention and Augmentation for Transformer-Based Histopathological Image Classification
Magnification-independent Histopathological Image Classification with Similarity-based Multi-scale Embeddings
DiagSet: a dataset for prostate cancer histopathological image classification
GasHis-Transformer: A Multi-scale Visual Transformer Approach for Gastric Histopathological Image Detection
Self-supervised driven consistency training for annotation efficient histopathology image analysis
UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading
Magnification Generalization for Histopathology Image Embedding
MS-GWNN:multi-scale graph wavelet neural network for breast cancer diagnosis
C-Net: A Reliable Convolutional Neural Network for Biomedical Image Classification
Graph Neural Networks for UnsupervisedDomain Adaptation of Histopathological ImageAnalytics
HATNet: An End-to-End Holistic Attention Network for Diagnosis of Breast Biopsy Images
Batch-Incremental Triplet Sampling for Training Triplet Networks Using Bayesian Updating Theorem
Offline versus Online Triplet Mining based on Extreme Distances of Histopathology Patches
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case Study
Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networks
Texture CNN for Histopathological Image Classification
Regression Concept Vectors for Bidirectional Explanations in Histopathology
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.