閱讀筆記：Visual comfort assessment for stereoscopic images based on sparse coding with multi-scale dict
Visual comfort assessment for stereoscopic images based on sparse coding with multi-scale dictionaries 題目：基於多尺度稀疏編碼字典的立體圖像舒適度評價 方法步驟：1.建立舒適度級別的多尺度字典2.估計測試樣本屬於每個級別的概率3.尋找概率對應的權重係數，求最後的舒適度分數 傳統方法的缺點：（傳統
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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：A Visual Comfort Assessment Approach of Stereoscopic Images based on Random Forest Regressor
- 3. 閱讀筆記:Binocular Fusion Net: Deep Learning Visual Comfort Assessment for Stereoscopic 3D
- 4. 閱讀筆記：VISUALCOMFORTASSESSMENTOFSTEREOSCOPICIMAGES USINGDEEPVISUALANDDISPARITYFEATURESBAS
- 5. 閱讀筆記：Visual comfort evaluated by hue asymmetries in stereoscopic images
- 6. 閱讀筆記：3D visual discomfort predictor based on subjective perceived-constraint sparse representation
- 7. 論文閱讀筆記---MSTGAR: Multioperator-Based Stereoscopic Thumbnail Generation With Arbitrary Resolution
- 8. Visual saliency detection based on multiscale deep cnn features
- 9. 《A sparse annotation strategy based on attention-guided active learning for 3D medic》--閱讀筆記-Arxiv
- 10. [論文]Light Field Compression with Disparity Guided Sparse Coding based on Structural Key Views