Abstract: Knowledge distillation has emerged as a primary solution for anomaly detection, leveraging feature discrepancies between teacher–student (T–S) networks to locate anomalies. However, previous ...
Abstract: The high-speed mobile networks offer great potentials to many future intelligent applications, such as autonomous vehicles in smart transportation systems. Such networks provide the ...
Abstract: Smart wearable devices benefit from lightweight deep neural networks (DNNs) with small silicon footprints for efficient real-time processing. While compression techniques are often applied ...
Abstract: Efficient medical image segmentation aims to provide accurate pixel-wise predictions with a lightweight implementation framework. However, existing lightweight networks generally overlook ...
Official implementation of our CleanPose, the first solution to mitigate the confoundering effect in category-level pose estimation via causal learning and knowledge distillation. You can generate the ...
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