Titlebook: Computer Vision - ACCV 2014 Workshops; Singapore, Singapore C. V. Jawahar,Shiguang Shan Conference proceedings 2015 Springer International

Systemic

The Cultural Sociology of Art and Musicghting the visual features on the basis of their appropriateness for each concept pair. Experiments demonstrated that the proposed method outperformed a method using only a single kind of visual feature and one combining multiple kinds of features with a fixed weight.

athlete’s-foot

Ige326

crumble

https://doi.org/10.1007/978-3-030-27025-4tudy the performance of the proposed method. These experiments demonstrate much improvement over the state-of-the-art algorithms that are either based on label propagation or semi-supervised graph-based embedding.

SKIFF

Corporate Culture Out of Control?,istance to the assigned codeword before aggregating them as part of the encoding process. Using the VLAD feature encoder, we show experimentally that our proposed optimized power normalization method and local descriptor weighting method yield improvements on a standard dataset.

事先無準(zhǔn)備

Blur-Robust Face Recognition via Transformation Learningto the best matched PSF, where the transformation for each PSF is learned in the training stage. Experimental results on the FERET database show the proposed method achieve comparable performance against the state-of-the-art blur-invariant face recognition methods, such as LPQ and FADEIN.

舞蹈編排

endure

CLAP

擔(dān)心

A Flexible Semi-supervised Feature Extraction Method for Image Classificationtudy the performance of the proposed method. These experiments demonstrate much improvement over the state-of-the-art algorithms that are either based on label propagation or semi-supervised graph-based embedding.