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Found 8 papers, 1 papers with code
Deep learning approaches in food recognition
Automatic image-based food recognition is a particularly challenging task.
UniMorph 4.0: Universal Morphology
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
Morphologically annotated corpora of Pomak
The project XXXX is developing a platform to enable researchers of living languages to easily create and make available state-of-the-art spoken and textual annotated resources.
Dens-PU: PU Learning with Density-Based Positive Labeled Augmentation
Once a set of negative samples is obtained, the PU learning problem reduces to binary classification.
Defect detection using weakly supervised learning
In many real-world scenarios, obtaining large amounts of labeled data can be a daunting task.
Deep learning based black spot identification on Greek road networks
This study focused on traffic accidents in Greek road networks to recognize black spots, utilizing data from police and government-issued car crash reports.
Towards Explainability in Monocular Depth Estimation
This paper focuses on the explainability in monocular depth estimation methods, in terms of how humans perceive depth.
Locality enhanced dynamic biasing and sampling strategies for contextual ASR
During training, a list of biasing phrases are selected from a large pool of phrases following a sampling strategy.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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