Titlebook: Computer Vision; Second CCF Chinese C Jinfeng Yang,Qinghua Hu,Deyu Meng Conference proceedings 2017 Springer Nature Singapore Pte Ltd. 2017

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書目名稱Computer Vision影響因子(影響力)




書目名稱Computer Vision影響因子(影響力)學(xué)科排名




書目名稱Computer Vision網(wǎng)絡(luò)公開度




書目名稱Computer Vision網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Vision被引頻次




書目名稱Computer Vision被引頻次學(xué)科排名




書目名稱Computer Vision年度引用




書目名稱Computer Vision年度引用學(xué)科排名




書目名稱Computer Vision讀者反饋




書目名稱Computer Vision讀者反饋學(xué)科排名

Aviary

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Massively Parallel Image Index for Vocabulary Tree Based Image Retrievalibutions include tree structure transformation, image package processing and task parallelism. Our GPU-based image index is up?to around thirty times faster than the original method and the whole GPU-based vocabulary tree algorithm is improved by twenty percentage in speed.

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Conference proceedings 2017assessment and analysis; image restoration; image segmentation and classification; image-based modeling; object detection and classification; object identification; photography and video; robot vision; shape representation and matching; statistical methods and learning; video analysis and event recognition; visual salient detection

Ferritin

Jean-Sébastien Coron,Hilder V. L. Pereirause 3D Dense Face Alignment (3DDFA) to obtain a fitted 3D morphable model, which is constrained by matching keypoints. From our experiments, a large pore-to-pore correspondence dataset, including 17,136 classes of matched pore-keypoint pairs, is established.

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Advances in Cryptology – ASIACRYPT 2020triadic autoencoder with deep architecture is developed for the shared and specific factors learning. Extensive experiments are conducted for cross-modal retrieval and multi-model clustering, which clearly demonstrate the effectiveness of our model.

MERIT

https://doi.org/10.1007/978-3-030-64840-4 an iterative optimizing algorithm is designed. Experimental results on cross-modal retrieval have shown the superiority of UDM over the compared approaches and the rapid convergence speed of the optimizing algorithm.

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