Abstract: In real-world scenarios with predominant dynamic objects, achieving robust and accurate positioning using Visualinertial navigation systems (VINS) poses a challenge because these objects ...
Abstract: Under the background of low-carbon transition, the development of renewable energy is an inevitable trend, making an increasing demand for flexibility. Multi-energy Aggregators (MEA) with ...
Abstract: To more effectively address the computational and memory requirements of deep neural networks (DNNs), leveraging multi-level sparsity-including value-level and bit-level sparsity-has emerged ...
Abstract: Multi-sensor fusion stands as a pivotal approach for enhancing the efficacy of 3D object detection in the context of autonomous driving. Nowadays, the fusion methods are mainly based on BEV ...
Abstract: Recent Multi-modal Large Language Models (MLLMs) have been challenged by the computational overhead resulting from massive video frames, often alleviated through compression strategies.
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