:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Zekang, Liu, Hong, Wang, Xiangdong
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	https://arxiv.org/abs/2407.00664
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

CARMIL: Context-Aware Regularization on Multiple Instance Learning models for Whole Slide Images
di: Saada, Thiziri Nait, et al.
Pubblicazione: (2024)

SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification
di: Qiu, Peijie, et al.
Pubblicazione: (2023)

Spatial Blindness in Whole-Slide Multiple Instance Learning
di: Li, Xiangyu, et al.
Pubblicazione: (2026)

Finding Regions of Interest in Whole Slide Images Using Multiple Instance Learning
di: Afonso, Martim, et al.
Pubblicazione: (2024)

GCE-MIL: Faithful and Recoverable Evidence for Multiple Instance Learning in Whole-Slide Imaging
di: Li, Xiangyu, et al.
Pubblicazione: (2026)

PTCMIL: Multiple Instance Learning via Prompt Token Clustering for Whole Slide Image Analysis
di: Zhao, Beidi, et al.
Pubblicazione: (2025)

SAC-MIL: Spatial-Aware Correlated Multiple Instance Learning for Histopathology Whole Slide Image Classification
di: Bai, Yu, et al.
Pubblicazione: (2025)

WsiCaption: Multiple Instance Generation of Pathology Reports for Gigapixel Whole-Slide Images
di: Chen, Pingyi, et al.
Pubblicazione: (2023)

ReaMIL: Reasoning- and Evidence-Aware Multiple Instance Learning for Whole-Slide Histopathology
di: Jung, Hyun Do, et al.
Pubblicazione: (2026)

Multiple Instance Learning for Glioma Diagnosis using Hematoxylin and Eosin Whole Slide Images: An Indian Cohort Study
di: Chauhan, Ekansh, et al.
Pubblicazione: (2024)

A Multicenter Benchmark of Multiple Instance Learning Models for Lymphoma Subtyping from HE-stained Whole Slide Images
di: Umer, Rao Muhammad, et al.
Pubblicazione: (2025)

PathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning
di: Zhou, Qifeng, et al.
Pubblicazione: (2024)

Morphology-Aware Prognostic model for Five-Year Survival Prediction in Colorectal Cancer from H&E Whole Slide Images
di: Sajjad, Usama, et al.
Pubblicazione: (2025)

Leveraging Transfer Learning and Multiple Instance Learning for HER2 Automatic Scoring of H\&E Whole Slide Images
di: Abdulsadig, Rawan S., et al.
Pubblicazione: (2024)

Efficient AI-Driven Multi-Section Whole Slide Image Analysis for Biochemical Recurrence Prediction in Prostate Cancer
di: Cho, Yesung, et al.
Pubblicazione: (2026)

MsaMIL-Net: An End-to-End Multi-Scale Aware Multiple Instance Learning Network for Efficient Whole Slide Image Classification
di: Wen, Jiangping, et al.
Pubblicazione: (2025)

CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images
di: Fourkioti, Olga, et al.
Pubblicazione: (2023)

MambaBack: Bridging Local Features and Global Contexts in Whole Slide Image Analysis
di: Chen, Sicheng, et al.
Pubblicazione: (2026)

A Multimodal Object-level Contrast Learning Method for Cancer Survival Risk Prediction
di: Yang, Zekang, et al.
Pubblicazione: (2024)

Self-Contrastive Weakly Supervised Learning Framework for Prognostic Prediction Using Whole Slide Images
di: Fuster, Saul, et al.
Pubblicazione: (2024)

SMILE: a Scale-aware Multiple Instance Learning Method for Multicenter STAS Lung Cancer Histopathology Diagnosis
di: Pan, Liangrui, et al.
Pubblicazione: (2025)

Cluster-Level Sparse Multi-Instance Learning for Whole-Slide Images
di: Zhang, Yuedi, et al.
Pubblicazione: (2025)

MiCo: Multiple Instance Learning with Context-Aware Clustering for Whole Slide Image Analysis
di: Li, Junjian, et al.
Pubblicazione: (2025)

CAPRMIL: Context-Aware Patch Representations for Multiple Instance Learning
di: Lolos, Andreas, et al.
Pubblicazione: (2025)

Hypergraph Mamba for Efficient Whole Slide Image Understanding
di: Lu, Jiaxuan, et al.
Pubblicazione: (2025)

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification
di: Zhang, Yunlong, et al.
Pubblicazione: (2023)

HookMIL: Revisiting Context Modeling in Multiple Instance Learning for Computational Pathology
di: Ling, Xitong, et al.
Pubblicazione: (2025)

WSI-VQA: Interpreting Whole Slide Images by Generative Visual Question Answering
di: Chen, Pingyi, et al.
Pubblicazione: (2024)

SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding
di: Chen, Ying, et al.
Pubblicazione: (2024)

Multimodal Distillation-Driven Ensemble Learning for Long-Tailed Histopathology Whole Slide Images Analysis
di: Ling, Xitong, et al.
Pubblicazione: (2025)

Advancing Multiple Instance Learning with Continual Learning for Whole Slide Imaging
di: Li, Xianrui, et al.
Pubblicazione: (2025)

PathNavigate: A Training-Free Pathology Agent with Surprise-Guided Scan and Shared Slide Memory for Whole-Slide Image VQA
di: Yang, Chunze, et al.
Pubblicazione: (2026)

Region-Affinity Attention for Whole-Slide Breast Cancer Classification in Deep Ultraviolet Imaging
di: Shaik, Nagur Shareef, et al.
Pubblicazione: (2026)

Agent Aggregator with Mask Denoise Mechanism for Histopathology Whole Slide Image Analysis
di: Ling, Xitong, et al.
Pubblicazione: (2024)

Summary of Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images
di: Amuda, Kamorudeen A., et al.
Pubblicazione: (2024)

PATHS: A Hierarchical Transformer for Efficient Whole Slide Image Analysis
di: Buzzard, Zak, et al.
Pubblicazione: (2024)

TAKT: Target-Aware Knowledge Transfer for Whole Slide Image Classification
di: Xiong, Conghao, et al.
Pubblicazione: (2023)

Fourier Transform Multiple Instance Learning for Whole Slide Image Classification
di: Bilic, Anthony, et al.
Pubblicazione: (2025)

ASMIL: Attention-Stabilized Multiple Instance Learning for Whole Slide Imaging
di: Ye, Linfeng, et al.
Pubblicazione: (2026)

Multiple Instance Learning with random sampling for Whole Slide Image Classification
di: Keshvarikhojasteh, H., et al.
Pubblicazione: (2024)