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论文解读 SpikeVideoFormer

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该文本介绍了 SpikeVideoFormer, 一种新型的脉冲驱动视频Transformer,旨在提升脉冲神经网络(SNNs)在视频任务中的性能,同时保持高能效。它提出了一种脉冲驱动的汉明注意力(SDHA)机制,该机制理论上能更好地捕捉脉冲特征间的相似性,并实现了线性时间复杂度。研究表明,该模型在视频分类、人体姿态追踪和视频语义分割等任务上,不仅超越了现有SNN方法,还在效率上显著优于人工神经网络(ANNs),展现了其在处理大量视频数据时的潜力。

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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