Abstract: Deploying LiDAR-based detectors on edge devices presents significant challenges due to limited computing power and memory. Post-training quantization (PTQ) requires only a small dataset for ...
Abstract: In autonomous driving, achieving rapid detection of target categories and locations is a key technology. However, the data volume of radar point clouds is enormous, and processing efficiency ...
Abstract: Point cloud instance segmentation is crucial for 3D scene understanding in robotics. However, existing methods heavily rely on learning-based approaches that require large amounts of ...
Abstract: This paper presents a digital compute-in-memory (CIM) macro for accelerating deep neural networks. The macro provides high-precision computation required for training deep neural networks ...
In this exclusive edition of In the Shadows, Scripps News correspondent Jason Bellini travels halfway around the world for unprecedented access to America’s most secretive warriors — the U.S. Special ...
Abstract: The authors propose a heterogeneous floating-point (FP) computing architecture to maximize energy efficiency by separately optimizing exponent processing and mantissa processing. The ...
Don't miss our top stories and need-to-know news everyday in your inbox. Ben Julian, owner of Precision Point Armory, decided to start his business because he saw how many people were intimidated by ...
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