(Review cs231n) Spatial Localization and Detection（classification and localization）
重在圖像的定位和檢測的內容。 一張圖片中只有一種給定類別標籤的對象，定位則是圖像中有對象框；再這些類中，每一個訓練目標都有一個類和許多的圖像內部對應類的位置選框。 猜想的僅是類標籤，不如說它們是位置選框。正確的位置選框，代表你的結果很接近分割的準確率。 研究定位的簡單有用基礎的範式，就是迴歸。 這張圖片經過一系列的處理過程，最終生成四個代表選框大小的實數，有很多不同的參數來描述選框，人們常用的是
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相關文章
- 1. 【CS231n筆記】08 Spatial Localization and Detection
- 2. Localization and Object Detection
- 3. .Net Globalization and Localization
- 4. DL-semantic segmentation/Classification+Localization/Object Detection/Instance Segmentation
- 5. 目標檢測分類和定位：Rethinking Classification and Localization for Object Detection
- 6. 《Double-Head RCNN: Rethinking Classification and Localization for Object Detection》論文詳解
- 7. 《SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization》
- 8. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
- 9. Online Object Detection and Localization on Stereo Visual SLAM System
- 10. 【OverFeat】《OverFeat：Integrated Recognition, Localization and Detection using Convolutional Networks》