Titlebook: Computer Vision – ACCV 2016 Workshops; ACCV 2016 Internatio Chu-Song Chen,Jiwen Lu,Kai-Kuang Ma Conference proceedings 2017 Springer Intern

旧石器时代

脾气暴躁的人

CNN-GRNN for Image Sharpness Assessment machine learning, CNN-GRNN fuses feature extraction and score prediction into an optimization procedure. Experiments on Gaussian blurring images in LIVE, CSIQ, TID2008 and TID2013 show that CNN-GRNN outperforms the state-of-the-art algorithms and gets closer to human subjective judgment.

MAUVE

diathermy

intimate

A Study of Combining Re-coloring and Adding Patterns to Images for Dichromatso add patterns according to the degree of deformation, and then re-color images overlaid with patterns. In the evaluation, we verify effectiveness of combining adding patterns and re-coloring, and demonstrate content-dependent characteristics through the studies based on different types of images and different types of patterns.

ICLE

Emotion Understanding Using Multimodal Information Based on Autobiographical Memories for Alzheimer’icits of AD patients. This work uses novel EEG features based on quaternions, facial landmarks and the combination of them. Their performance was evaluated in a comparative study with a state of the art methods that demonstrates the proposed approach.

招募

Blind Image Deblurring Using Elastic-Net Based Rank Priorelastic-net regularization of singular values. We quantitatively verify that it favors clear images over blurred images. This property is able to facilitate the kernel estimation in the conventional maximum a posterior framework. Based on this prior, we develop an efficient optimization method to so

indubitable

precede

取回

CNN-GRNN for Image Sharpness AssessmentSA) is useful and challenging. In this paper, a shallow convolutional neural network (CNN) is proposed for intrinsic representation of image sharpness and general regression neural network (GRNN) is utilized for precise score prediction. The hybrid CNN-GRNN model tends to build functional relationsh