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cryolo_nets [2018/12/21 15:16]
twagner [Network #3 PhosaurusNet]
cryolo_nets [2018/12/24 10:15] (current)
twagner [Introduction]
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 The main components are **convolutional operations** and **max pooling operations**:​ The main components are **convolutional operations** and **max pooling operations**:​
-  * Convolutional layer: A convolutional learn local patterns. For 2D images, these are patterns in small region ​in of the input image. In the YOLO architecture,​ these are 1x1 or 3x3 windows. The output of a convolutional layer is called feature map.+  * Convolutional layer: A convolutional learn local patterns. For 2D images, these are patterns in small region of the input image. In the YOLO architecture,​ these are 1x1 or 3x3 windows. The output of a convolutional layer is called feature map.
   * Max-pooling operation: Max-pooling operations downsampling the feature maps of previous layers. This enables the following convolutional layers to see a larger extends of the input image.   * Max-pooling operation: Max-pooling operations downsampling the feature maps of previous layers. This enables the following convolutional layers to see a larger extends of the input image.
 Another characteristic of this architecture is the passthrough connection between 13 and 21. it helps the network to utilize low level features during detection. Another characteristic of this architecture is the passthrough connection between 13 and 21. it helps the network to utilize low level features during detection.