Transformer 架构因其强大的通用性而备受瞩目，它能够处理文本、图像或任何类型的数据及其组合。其核心的“Attention”机制通过计算序列中每个 token 之间的自相似性，从而实现对各种类型数据的总结和生成。在 Vision Transformer 中，图像首先被分解为正方形图像块 ...

The self-attention-based transformer model was first introduced by Vaswani et al. in their paper Attention Is All You Need in 2017 and has been widely used in natural language processing. A ...

Vision AI Has Moved Beyond CNNs—Now What? Convolutional Neural Networks (CNNs) have long dominated AI vision, powering applications from automotive ADAS to face recognition and surveillance. But the ...

Vision transformers (ViTs) are powerful artificial intelligence (AI) technologies that can identify or categorize objects in images -- however, there are significant challenges related to both ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...