Weakly supervised object localization and detection: A survey
As an emerging and challenging problem in the computer vision community, weakly
supervised object localization and detection plays an important role for develo** new …
supervised object localization and detection plays an important role for develo** new …
Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self …
Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
Dtfd-mil: Double-tier feature distillation multiple instance learning for histopathology whole slide image classification
Multiple instance learning (MIL) has been increasingly used in the classification of
histopathology whole slide images (WSIs). However, MIL approaches for this specific …
histopathology whole slide images (WSIs). However, MIL approaches for this specific …
Transmil: Transformer based correlated multiple instance learning for whole slide image classification
Multiple instance learning (MIL) is a powerful tool to solve the weakly supervised
classification in whole slide image (WSI) based pathology diagnosis. However, the current …
classification in whole slide image (WSI) based pathology diagnosis. However, the current …
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
We address the challenging problem of whole slide image (WSI) classification. WSIs have
very high resolutions and usually lack localized annotations. WSI classification can be cast …
very high resolutions and usually lack localized annotations. WSI classification can be cast …
Hopfield networks is all you need
We introduce a modern Hopfield network with continuous states and a corresponding
update rule. The new Hopfield network can store exponentially (with the dimension of the …
update rule. The new Hopfield network can store exponentially (with the dimension of the …
Learning self-consistency for deepfake detection
We propose a new method to detect deepfake images using the cue of the source feature
inconsistency within the forged images. It is based on the hypothesis that images' distinct …
inconsistency within the forged images. It is based on the hypothesis that images' distinct …
Attention-based deep multiple instance learning
Multiple instance learning (MIL) is a variation of supervised learning where a single class
label is assigned to a bag of instances. In this paper, we state the MIL problem as learning …
label is assigned to a bag of instances. In this paper, we state the MIL problem as learning …
Interventional bag multi-instance learning on whole-slide pathological images
Multi-instance learning (MIL) is an effective paradigm for whole-slide pathological images
(WSIs) classification to handle the gigapixel resolution and slide-level label. Prevailing MIL …
(WSIs) classification to handle the gigapixel resolution and slide-level label. Prevailing MIL …
Catching both gray and black swans: Open-set supervised anomaly detection
Despite most existing anomaly detection studies assume the availability of normal training
samples only, a few labeled anomaly examples are often available in many real-world …
samples only, a few labeled anomaly examples are often available in many real-world …