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Seeing unseen: Discover novel biomedical concepts via geometry-constrained probabilistic modeling
Abstract Machine learning holds tremendous promise for transforming the fundamental
practice of scientific discovery by virtue of its data-driven nature. With the ever-increasing …
practice of scientific discovery by virtue of its data-driven nature. With the ever-increasing …
Revisiting Unsupervised Temporal Action Localization: The Primacy of High-Quality Actionness and Pseudolabels
Recently, temporal action localization (TAL) methods, especially the weakly-supervised and
unsupervised ones, have become a hot research topic. Existing unsupervised methods …
unsupervised ones, have become a hot research topic. Existing unsupervised methods …
Progressive transformation learning for leveraging virtual images in training
To effectively interrogate UAV-based images for detecting objects of interest, such as
humans, it is essential to acquire large-scale UAV-based datasets that include human …
humans, it is essential to acquire large-scale UAV-based datasets that include human …
A survey on open-set image recognition
Open-set image recognition (OSR) aims to both classify known-class samples and identify
unknown-class samples in the testing set, which supports robust classifiers in many realistic …
unknown-class samples in the testing set, which supports robust classifiers in many realistic …
Open-Set Text Recognition Implementations (III): Open-set Predictor
This chapter discusses the approaches of the representation-prototype matching process,
which is used to recognize or reject the corresponding samples in question. For each query …
which is used to recognize or reject the corresponding samples in question. For each query …
Learning for transductive threshold calibration in open-world recognition
In deep metric learning for visual recognition the calibration of distance thresholds is crucial
for achieving desired model performance in the true positive rates (TPR) or true negative …
for achieving desired model performance in the true positive rates (TPR) or true negative …
Open-world dynamic prompt and continual visual representation learning
The open world is inherently dynamic, characterized by ever-evolving concepts and
distributions. Continual learning (CL) in this dynamic open-world environment presents a …
distributions. Continual learning (CL) in this dynamic open-world environment presents a …