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Found 5 papers, 2 papers with code
HSViT: Horizontally Scalable Vision Transformer
While the Vision Transformer (ViT) architecture gains prominence in computer vision and attracts significant attention from multimedia communities, its deficiency in prior knowledge (inductive bias) regarding shift, scale, and rotational invariance necessitates pre-training on large-scale datasets.
Deep Learning Techniques for Video Instance Segmentation: A Survey
Video instance segmentation, also known as multi-object tracking and segmentation, is an emerging computer vision research area introduced in 2019, aiming at detecting, segmenting, and tracking instances in videos simultaneously.
An Efficient and Reliable Asynchronous Federated Learning Scheme for Smart Public Transportation
Asynchronous Federated Learning (AFL) is a scheme that reduces the latency of aggregation to improve efficiency, but the learning performance is unstable due to unreasonably weighted local models.
SCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems
Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy.
Learning convolutional neural network to maximize Pos@Top performance measure
The CNN model is used to represent the multi-instance data point, and a classifier function is used to predict the label from the its CNN representation.
