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Found 4 papers, 1 papers with code
Predicting Traffic Flow with Federated Learning and Graph Neural with Asynchronous Computations Network
Our framework incorporates the principles of asynchronous graph convolutional networks with federated learning to enhance the accuracy and efficiency of real-time traffic flow prediction.
EZ-CLIP: Efficient Zeroshot Video Action Recognition
Recent advancements in large-scale pre-training of visual-language models on paired image-text data have demonstrated impressive generalization capabilities for zero-shot tasks.
Metricizing the Euclidean Space towards Desired Distance Relations in Point Clouds
Given a set of points in the Euclidean space $\mathbb{R}^\ell$ with $\ell>1$, the pairwise distances between the points are determined by their spatial location and the metric $d$ that we endow $\mathbb{R}^\ell$ with.
Localization of Unmanned Aerial Vehicles in Corridor Environments using Deep Learning
When the UAV is at the center of the corridor, a new image is passed through another trained DNN to predict the orientation of the UAV with respect to the CBL of the corridor.
