閱讀筆記：VISUALCOMFORTASSESSMENTOFSTEREOSCOPICIMAGES USINGDEEPVISUALANDDISPARITYFEATURESBAS
題目：基於人體注意力的深度視覺和視差特徵的立體圖像舒適度評估 特徵選取：視差大小和梯度特徵 訓練方法：深度卷積神經網絡 數據庫：IEEE-SA 總體框圖： 其中，deep siamese network:深度級聯網絡；differential微分； 實驗： 1. 2.
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相關文章
- 1. 閱讀筆記：VISUAL COMFORT ASSESSMENT FOR STEREOSCOPIC 3D IMAGES BASED ON SALIENT DISCOMFORT REGIONS
- 2. 閱讀筆記:Binocular Fusion Net: Deep Learning Visual Comfort Assessment for Stereoscopic 3D
- 3. 閱讀筆記：A Visual Comfort Assessment Approach of Stereoscopic Images based on Random Forest Regressor
- 4. 閱讀筆記：Visual comfort assessment for stereoscopic images based on sparse coding with multi-scale dict
- 5. 閱讀筆記：Visual comfort evaluated by hue asymmetries in stereoscopic images
- 6. 閱讀筆記：3D Visual Discomfort Predictor: Analysis of Horizontal Disparity and Neural Activity Statistics
- 7. [解讀] Deep Clustering for Unsupervised Learning of Visual Features
- 8. 論文閱讀《Deep Learning Assessment of Tumor Proliferation in Breast Cancer Histological Images》
- 9. Deep Clustering for Unspervised Learning of Visual Features
- 10. 論文閱讀筆記（audio-visual相關）—Co-Separating Sounds of Visual Objects