研究人员开发了一种新颖的任意时刻计算方法，用于处理激光雷达数据以进行3D目标检测的深度神经网络。该方法允许动态缩放输入分辨率，使模型能够调整处理级别以满足实时时序要求，而无需多个训练模型。一个面向截止时间的调度器预测不同分辨率的执行时间，在nuScenes等数据集上优化性能，并在模拟自动驾驶系统中展示了改进的无碰撞导航。 AI
影响 通过优化激光雷达数据处理，增强了自主系统的实时性能。
排序理由 该集群包含一篇在arXiv上发表的研究论文，详细介绍了一种新颖的深度神经网络方法。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2607.08391v1 Announce Type: cross Abstract: Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been shown to enhance the performance of cyber-physical systems. In this work, we focus o…
Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been shown to enhance the performance of cyber-physical systems. In this work, we focus on enabling anytime computing for deep neural netwo…