Computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review
Prostate cancer is the second most diagnosed cancer of men all over the world. In the last
few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have …
few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have …
On the role and the importance of features for background modeling and foreground detection
Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …
applications in video surveillance. Background modeling methods have become increasing …
Accurate object localization in remote sensing images based on convolutional neural networks
Y Long, Y Gong, Z **ao, Q Liu - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
In this paper, we focus on tackling the problem of automatic accurate localization of detected
objects in high-resolution remote sensing images. The two major problems for object …
objects in high-resolution remote sensing images. The two major problems for object …
Local binary features for texture classification: Taxonomy and experimental study
Abstract Local Binary Patterns (LBP) have emerged as one of the most prominent and
widely studied local texture descriptors. Truly a large number of LBP variants has been …
widely studied local texture descriptors. Truly a large number of LBP variants has been …
Rigid-motion scattering for texture classification
A rigid-motion scattering computes adaptive invariants along translations and rotations, with
a deep convolutional network. Convolutions are calculated on the rigid-motion group, with …
a deep convolutional network. Convolutions are calculated on the rigid-motion group, with …
Joint representation learning and keypoint detection for cross-view geo-localization
In this paper, we study the cross-view geo-localization problem to match images from
different viewpoints. The key motivation underpinning this task is to learn a discriminative …
different viewpoints. The key motivation underpinning this task is to learn a discriminative …
Deeply learned attributes for crowded scene understanding
Crowded scene understanding is a fundamental problem in computer vision. In this study,
we develop a multi-task deep model to jointly learn and combine appearance and motion …
we develop a multi-task deep model to jointly learn and combine appearance and motion …
Spontaneous facial micro-expression analysis using spatiotemporal completed local quantized patterns
Spontaneous facial micro-expression analysis has become an active task for recognizing
suppressed and involuntary facial expressions shown on the face of humans. Recently …
suppressed and involuntary facial expressions shown on the face of humans. Recently …
Lbp with six intersection points: Reducing redundant information in lbp-top for micro-expression recognition
Facial micro-expression recognition is an upcoming area in computer vision research. Up
until the recent emergence of the extensive CASMEII spontaneous micro-expression …
until the recent emergence of the extensive CASMEII spontaneous micro-expression …
Pairwise rotation invariant co-occurrence local binary pattern
Designing effective features is a fundamental problem in computer vision. However, it is
usually difficult to achieve a great tradeoff between discriminative power and robustness …
usually difficult to achieve a great tradeoff between discriminative power and robustness …