官术网_书友最值得收藏!

Pooling layer

Another process that makes processing capability efficient is called pooling. In the pooling layer, larger images are pushed to shrink in size while keeping the information in them. This is done by sliding a window across the image and taking the maximum value in each window. In a typical pooling layer, a window of 2 or 3 pixels works on a side, but taking steps of 2 pixels also works:

After the pooling layer, the image size will be reduced by one quarter of what it was. This maintains the maximum value from each window. It also preserves the best feature inside every window. This step means that it doesn't care whether the feature fits or not, as long as it fits somewhere inside the window. With the help of this layer, CNN can identify whether a feature exists inside an image, instead of worrying about where it is. In this way, computers need not worry about being literal.

By the end of this layer, bringing down the size of an image from 10 megapixels to 2 megapixels will definitely help us to compute the capability of further processing faster.

主站蜘蛛池模板: 宣恩县| 澄迈县| 花莲市| 深州市| 高平市| 赞皇县| 洛浦县| 常州市| 湘潭市| 伊川县| 寻乌县| 莫力| 苍溪县| 禄劝| 鹤山市| 黔南| 三门峡市| 额济纳旗| 双柏县| 布尔津县| 安乡县| 那曲县| 林州市| 雷山县| 崇礼县| 即墨市| 南部县| 双桥区| 新田县| 开远市| 阿巴嘎旗| 磴口县| 四子王旗| 白山市| 天台县| 四平市| 丹东市| 博罗县| 南昌市| 永清县| 温宿县|