January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Attention models
Attention mechanisms in neural networks are (very) loosely based on the visual attention mechanism found in humans. The idea is to focus on different parts of the inputs as the algorithm tries to make and refine prediction each time.
In computer vision, attention means the ability to attend/focus on a certain region of an image with high resolution while perceiving the surrounding image in low resolution to get better understanding of the salient content, and then adjusting the focal point over time. There are a few benefits of introducing the attention model into image understanding.
First, it helps the model to focus on only the salient or important objects or areas that matter to the viewer of the image (human or computer) ...
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