Copertina

MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Jovišić, Nikola, Škipina, Milica, Dall'Asen, Nicola, Ćulibrk, Dubravko
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

MAMBO: High-Resolution Generative Approach for Mammography Images
di: Škipina, Milica, et al.
Pubblicazione: (2025)

SetFlow: Generating Structured Sets of Representations for Multiple Instance Learning
di: Jovišić, Nikola, et al.
Pubblicazione: (2026)

Adv-KD: Adversarial Knowledge Distillation for Faster Diffusion Sampling
di: Mekonnen, Kidist Amde, et al.
Pubblicazione: (2024)

Retrieval-enriched zero-shot image classification in low-resource domains
di: Dall'Asen, Nicola, et al.
Pubblicazione: (2024)

AL-GTD: Deep Active Learning for Gaze Target Detection
di: Tonini, Francesco, et al.
Pubblicazione: (2024)

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

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

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

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

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

Mamba2MIL: State Space Duality Based Multiple Instance Learning for Computational Pathology
di: Zhang, Yuqi, et al.
Pubblicazione: (2024)

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)

From Weights to Concepts: Data-Free Interpretability of CLIP via Singular Vector Decomposition
di: Gentile, Francesco, et al.
Pubblicazione: (2026)

Multi-View Stenosis Classification Leveraging Transformer-Based Multiple-Instance Learning Using Real-World Clinical Data
di: Cenikj, Nikola, et al.
Pubblicazione: (2026)

Self-Supervised Multiple Instance Learning for Acute Myeloid Leukemia Classification
di: Kazeminia, Salome, et al.
Pubblicazione: (2024)

Shared Neural Space: Unified Precomputed Feature Encoding for Multi-Task and Cross Domain Vision
di: Li, Jing, et al.
Pubblicazione: (2025)

FMaMIL: Frequency-Driven Mamba Multi-Instance Learning for Weakly Supervised Lesion Segmentation in Medical Images
di: Cheng, Hangbei, et al.
Pubblicazione: (2025)

GAS-MIL: Group-Aggregative Selection Multi-Instance Learning for Ensemble of Foundation Models in Digital Pathology Image Analysis
di: Quan, Peiran, et al.
Pubblicazione: (2025)

Leveraging Gait Patterns as Biomarkers: An attention-guided Deep Multiple Instance Learning Network for Scoliosis Classification
di: Li, Haiqing, et al.
Pubblicazione: (2025)

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

Increasing the Utility of Synthetic Images through Chamfer Guidance
di: Dall'Asen, Nicola, et al.
Pubblicazione: (2025)

PRTGaussian: Efficient Relighting Using 3D Gaussians with Precomputed Radiance Transfer
di: Zhang, Libo, et al.
Pubblicazione: (2024)

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

Reducing Variability of Multiple Instance Learning Methods for Digital Pathology
di: Mammadov, Ali, 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)

Self-Supervision Enhances Instance-based Multiple Instance Learning Methods in Digital Pathology: A Benchmark Study
di: Mammadov, Ali, et al.
Pubblicazione: (2025)

Label-free Concept Based Multiple Instance Learning for Gigapixel Histopathology
di: Sun, Susu, et al.
Pubblicazione: (2025)

RetMIL: Retentive Multiple Instance Learning for Histopathological Whole Slide Image Classification
di: Chu, Hongbo, et al.
Pubblicazione: (2024)

Mammo-Clustering: A Multi-views Tri-level Information Fusion Context Clustering Framework for Localization and Classification in Mammography
di: Yang, Shilong, et al.
Pubblicazione: (2024)

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

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

WSD-MIL: Window Scale Decay Multiple Instance Learning for Whole Slide Image Classification
di: Feng, Le, et al.
Pubblicazione: (2025)

EnGraf-Net: Multiple Granularity Branch Network with Fine-Coarse Graft Grained for Classification Task
di: La Grassa, Riccardo, et al.
Pubblicazione: (2025)

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

Detecting Domain Shift in Multiple Instance Learning for Digital Pathology Using Fréchet Domain Distance
di: Pocevičiūtė, Milda, et al.
Pubblicazione: (2024)

Medical-Knowledge Driven Multiple Instance Learning for Classifying Severe Abdominal Anomalies on Prenatal Ultrasound
di: Liang, Huanwen, et al.
Pubblicazione: (2025)

IFAdapter: Instance Feature Control for Grounded Text-to-Image Generation
di: Wu, Yinwei, et al.
Pubblicazione: (2024)

Libra-MIL: Multimodal Prototypes Stereoscopic Infused with Task-specific Language Priors for Few-shot Whole Slide Image Classification
di: Zhuang, Zhenfeng, et al.
Pubblicazione: (2025)

GMAT: Grounded Multi-Agent Clinical Description Generation for Text Encoder in Vision-Language MIL for Whole Slide Image Classification
di: Quang, Ngoc Bui Lam, et al.
Pubblicazione: (2025)

MGRegBench: A Novel Benchmark Dataset with Anatomical Landmarks for Mammography Image Registration
di: Krasnova, Svetlana, et al.
Pubblicazione: (2025)