A comprehensive survey to face hallucination
This paper comprehensively surveys the development of face hallucination (FH), including
both face super-resolution and face sketch-photo synthesis techniques. Indeed, these two …
both face super-resolution and face sketch-photo synthesis techniques. Indeed, these two …
A survey on multi-view learning
In recent years, a great many methods of learning from multi-view data by considering the
diversity of different views have been proposed. These views may be obtained from multiple …
diversity of different views have been proposed. These views may be obtained from multiple …
Simultaneous spectral-spatial feature selection and extraction for hyperspectral images
In hyperspectral remote sensing data mining, it is important to take into account of both
spectral and spatial information, such as the spectral signature, texture feature, and …
spectral and spatial information, such as the spectral signature, texture feature, and …
Multitask autoencoder model for recovering human poses
Human pose recovery in videos is usually conducted by matching 2-D image features and
retrieving relevant 3-D human poses. In the retrieving process, the mapping between …
retrieving relevant 3-D human poses. In the retrieving process, the mapping between …
High-order distance-based multiview stochastic learning in image classification
How do we find all images in a larger set of images which have a specific content? Or
estimate the position of a specific object relative to the camera? Image classification …
estimate the position of a specific object relative to the camera? Image classification …
Semisupervised multiview distance metric learning for cartoon synthesis
In image processing, cartoon character classification, retrieval, and synthesis are critical, so
that cartoonists can effectively and efficiently make cartoons by reusing existing cartoon …
that cartoonists can effectively and efficiently make cartoons by reusing existing cartoon …
Exploiting click constraints and multi-view features for image re-ranking
Image re-ranking is effective in improving performance of text-based image searches.
However, improvements from existing re-ranking algorithms are limited by two factors: one is …
However, improvements from existing re-ranking algorithms are limited by two factors: one is …
Traffic sign segmentation and classification using statistical learning methods
JM Lillo-Castellano, I Mora-Jiménez… - Neurocomputing, 2015 - Elsevier
Traffic signs are an essential part of any circulation system, and failure detection by the
driver may significantly increase the accident risk. Currently, automatic traffic sign detection …
driver may significantly increase the accident risk. Currently, automatic traffic sign detection …
Topic-sensitive influencer mining in interest-based social media networks via hypergraph learning
Social media is emerging as a new mainstream means of interacting around online media.
Social influence mining in social networks is therefore of critical importance in real-world …
Social influence mining in social networks is therefore of critical importance in real-world …
Pairwise constraints based multiview features fusion for scene classification
Recently, we have witnessed a surge of interests of learning a low-dimensional subspace
for scene classification. The existing methods do not perform well since they do not consider …
for scene classification. The existing methods do not perform well since they do not consider …