<ul><li>A novel spatiotemporal learning framework for event-based object recognition is presented.</li><li>The framework utilizes a VGG network enhanced with Convolutional Block Attention Module (CBAM).</li><li>The approach achieves comparable performance to state-of-the-art ResNet-based methods while reducing parameter count.</li><li>Experimental results highlight the efficiency and effectiveness of the framework for real-world applications.</li></ul>

Spatiotemporal Attention Learning Framework for Event-Driven Object Recognition

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