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Found 6 papers, 1 papers with code
Universal Novelty Detection Through Adaptive Contrastive Learning
More precisely, for novelty detection, distribution shifts may occur in the training set or the test set.
The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection
As machine learning tasks continue to evolve, the trend has been to gather larger datasets and train increasingly larger models.
HealNet -- Self-Supervised Acute Wound Heal-Stage Classification
Identifying, tracking, and predicting wound heal-stage progression is a fundamental task towards proper diagnosis, effective treatment, facilitating healing, and reducing pain.
The multi-channel potentiostat: Development and Evaluation of a Scalable Mini-Potentiostat array for investigating electrochemical reaction mechanisms
As the design of electrochemical devices evolve applications for systems with multiple working electrodes have become more common.
Reciprocal Landmark Detection and Tracking with Extremely Few Annotations
The model is trained using few annotated frames across the entire cardiac cine sequence to generate consistent detection and tracking of landmarks, and an adversarial training for the model is proposed to take advantage of these annotated frames.
Adaptive Intelligent Secondary Control of Microgrids Using a Biologically-Inspired Reinforcement Learning
In this paper, a biologically-inspired adaptive intelligent secondary controller is developed for microgrids to tackle system dynamics uncertainties, faults, and/or disturbances.
