April 2020
Intermediate to advanced
816 pages
18h 32m
Chinese
Content preview from 精通機器學習
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470
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第十四章：使用摺積神經網路來製作深度電腦視覺
聯集
交集
預測
標籤
圖
14-23
外框的
Intersection over Union（IoU）
指標
知道如何分類和定位一個物體是很棒的事情
，
但如果圖裡面有多個物體呢
（
就像花朵資料
組那樣
）？
物體偵測
在圖像中分類和定位多個物體稱為
物體偵測
（object detection）。
直到幾年前
，
最常見的做
法仍然是使用被訓練來分類和定位單一物體的
CNN
來掃描圖像
，
如圖
14-24
所示
。
這個
例子中將圖像切成
6
×
8
的網格
，
再用一個
CNN（
粗的黑框
）
滑過全部的
3
×
3
區域
。
當
CNN
查看圖像的左上角時
，
它會偵測到最左邊的玫瑰的一部分
，
接著當它第一次往右移
一步時
，
再度偵測到同一朵玫瑰
。
在下一步
，
它開始偵測到最上面的玫瑰
，
當它往右再移
一步時
，
再次偵測到它
。
你可以繼續用
CNN
來掃描整張圖像
，
查看所有的
3 × 3
區域
。
此
外
，
因為物體可能有不同的大小
，
你也可以用
CNN
來掃描不同大小的區域
。
例如
，
當你
掃完
3 × 3
區域之後
，
也可以用
CNN
來掃描
4 × 4
區域
。
物體偵測
|
471
圖
14-24
用
CNN
來掃描圖像
，
藉以偵測多個物體
這項技術相當直觀
，
但如你所見
，
它會在稍微不同的位置偵測同一個物體多次
。
所以我們
必須進行一些事後的工作來捨棄沒必要的外框
，
常見的方法稱為 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.