HIGHLIGHTS
- What: This dataset does not contain the alphabet, which is the goal of this study. Each layer uses self-attention mechanisms to weigh the importance of different patches relative to each other, allowing the model to focus more on the most relevant parts of the image for the task at hand. The main reason for this bad performance is the limited amount of data. The first experiment consisted in the analysis of sign recognition when just the information about hands and fingers` position was considered.
- Who: Francisco Morillas-Espejo from the Department of Computer Science . . .
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