Search Results for author:
Found 6 papers, 3 papers with code
Novel Categories Discovery Via Constraints on Empirical Prediction Statistics
As an alternative to the traditional pseudo-labeling-based approaches, we leverage the connection between the data sampling and the provided multinoulli (categorical) distribution of novel classes.
A Systematic Study on Object Recognition Using Millimeter-wave Radar
Image and video data are light and weather-dependent, susceptible to the occlusion effect, and present privacy problems.
NEV-NCD: Negative Learning, Entropy, and Variance regularization based novel action categories discovery
During our experiments with UCF101 and multi-view action dataset, NEV-NCD achieves ~ 83% classification accuracy in test instances of labeled data.
Demo: RhythmEdge: Enabling Contactless Heart Rate Estimation on the Edge
In this demo paper, we design and prototype RhythmEdge, a low-cost, deep-learning-based contact-less system for regular HR monitoring applications.
Autonomous Warehouse Robot using Deep Q-Learning
In warehouses, specialized agents need to navigate, avoid obstacles and maximize the use of space in the warehouse environment.
Where were my keys? -- Aggregating Spatial-Temporal Instances of Objects for Efficient Retrieval over Long Periods of Time
Robots equipped with situational awareness can help humans efficiently find their lost objects by leveraging spatial and temporal structure.
