Visual saliency detection based on multiscale deep cnn features
Task 視覺顯著性 Visual Saliency（這篇文章2017年左右，很早了） 顯著性由視覺對比產生，直觀的表徵了圖像的某些部分與相鄰區域比較更突出。 本文發現，利用CNN提取的多尺度特徵具有較高視覺顯著性，在視覺識別方面取得了巨大成功。因此，本文引入了一種神經網絡結構，在CNN後跟着FC層，提取三種不同尺度（相互嵌套）的特徵（分別是考慮區域、相鄰區域和整個區域）。 另外，本文還構建了一個
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相關文章
- 1. 2017-04-18 Visual Saliency Detection Based on Multiscale Deep CNN Features
- 2. Summary of defect detection algorithms based on deep learning
- 3. Background Prior-Based Salient Object Detection via Deep Reconstruction Residual
- 4. saliency detection by forward and backward cues in deep-cnn
- 5. 2015-A Two-Stage Clustering Based 3D Visual Saliency
- 6. 《A Novel Detector Based on Convolution Neural Networks for Multiscale SAR Ship Detection in Complex》
- 7. An Introduction to CNN based Object Detection
- 8. PAMI 2010 Context-aware saliency detection
- 9. Cluster-based Co-saliency Detection筆記
- 10. Change Detection Based on Deep Siamese Convolutional Network for Optical Aerial Images