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State of the art paper

Shuang-Bo Sun, Zhi-Heng Zhang, Xin-Ling Dong, Heng-Ru Zhang, Tong-Jun Li, Lin Zhang, Fan Min
This paper proposes a new measure for recommendation through integrating Triangle and Jaccard similarities. The Triangle similarity considers both the length and the angle of rating vectors between them, while the Jaccard similarity considers non co-rating users. We compare the new similarity measure with eight state-of-the-art ones on four popular datasets under the leave-one-out scenario. Results show that the new measure outperforms all the counterparts in terms of the mean absolute error and the root mean square error...
2017: PloS One
Kun Song, Feiping Nie, Junwei Han, Xuelong Li
The amount of matrix data has increased rapidly nowadays. How to classify matrix data efficiently is an important issue. In this paper, by discovering the shortages of 2-D linear discriminant analysis and 2-D logistic regression, a novel 2-D framework named rank-k 2-D multinomial logistic regression (2DMLR-RK) is proposed. The 2DMLR-RK is designed for a multiclass matrix classification problem. In the proposed framework, each category is modeled by a left projection matrix and a right projection matrix with rank k...
August 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu
Random forests (RFs) are recognized as one type of ensemble learning method and are effective for the most classification and regression tasks. Despite their impressive empirical performance, the theory of RFs has yet been fully proved. Several theoretically guaranteed RF variants have been presented, but their poor practical performance has been criticized. In this paper, a novel RF framework is proposed, named Bernoulli RFs (BRFs), with the aim of solving the RF dilemma between theoretical consistency and empirical performance...
August 15, 2017: IEEE Transactions on Neural Networks and Learning Systems
Zezhou Cheng, Qingxiong Yang, Bin Sheng
This paper investigates into the colorization problem which converts a grayscale image to a colorful version. This is a difficult problem and normally requires manual adjustment to achieve artifact-free quality. For instance, it normally requires human-labelled color scribbles on the grayscale target image or a careful selection of colorful reference images. The recent learning-based colorization techniques automatically colorize a grayscale image using a single neural network. Since different scenes usually have distinct color styles, it is difficult to accurately capture the color characteristics using a single neural network...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Jiao Wu, Feilong Cao, Juncheng Yin
A novel multi-morphological representation model for solving the nonlocal similarity-based image reconstruction from compressed measurements is introduced in this paper. Under the probabilistic framework, the proposed approach provides the nonlocal similarity clustering for image patches by using the Gaussian mixture models, and endows a multimorphological representation for image patches in each cluster by using the Gaussians that represent the different features to model the morphological components. Using the simple alternating iteration, the developed piecewise morphological diversity estimation (PMDE) algorithm can effectively estimate the MAP of morphological components, thus resulting in the nonlinear estimation for image patches...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Hanhui Li, Hefeng Wu, Huifang Zhang, Shujin Lin, Xiaonan Luo, Ruomei Wang
Recently, correlation filter (CF) based tracking methods have attracted considerable attention because of their high-speed performance. However, distortion, which refers to the phenomenon that the correlation outputs of CF based trackers are distorted, remains a major obstacle for these methods. In this paper, we propose a Distortion-Aware Correlation Filter (DACF) framework, which can detect distortions and recover from tracking failures. Our framework employs a simple yet effective feature termed normed correlation response to detect distortions...
August 14, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Chun-Hao Huang, Benjamin Allain, Edmond Boyer, Jean-Sebastien Franco, Federico Tombari, Nassir Navab, Slobodan Ilic
3D Human shape tracking consists in fitting a template model to temporal sequences of visual observations. It usually comprises an association step, that finds correspondences between the model and the input data, and a deformation step, that fits the model to the observations given correspondences. Most current approaches follow the Iterative-Closest-Point (ICP) paradigm, where the association step is carried out by searching for the nearest neighbors. It fails when large deformations occur and errors in the association tend to propagate over time...
August 15, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Marcos A Mouriño-García, Roberto Pérez-Rodríguez, Luis E Anido-Rifón
OBJECTIVES: The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space...
August 16, 2017: Methods of Information in Medicine
T Pilissy, A Toth, G Fazekas, A Sobjak, R Rosenthal, T Luftenegger, P Panek, P Mayer
In the recent decades state of the art technologies appeared in many areas to assist older adults with disabilities. However, one very essential activity of daily life, the toileting remained without any relevant development. The iToilet project of the European Union focuses on the development of an intelligent and motorized toilet system to enable independent toilet use for older adults with disabilities. To begin the development, the user requirements of end-users were assessed by means of focus group interviews and questionnaires...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
Florian Loffing, Rouwen Cañal-Bruland
Anticipation has become an increasingly important research area within sport psychology since its infancy in the late 1970s. Early work has increased our fundamental understanding of skilled anticipation in sports and how this skill is developed. With increasing theoretical and practical insights and concurrent technological advancements, researchers are now able to tackle more detailed questions with sophisticated methods. Despite this welcomed progress, some fundamental questions and challenges remain to be addressed, including the (relative) contributions of visual and motor experience to anticipation, intraindividual and interindividual variation in gaze behaviour, and the impact of non-kinematic (contextual or situational) information on performance and its interaction with advanced kinematic cues during the planning and execution of (re)actions in sport...
August 2017: Current Opinion in Psychology
Cong Shen, Yijie Ding, Jijun Tang, Xinying Xu, Fei Guo
The prediction of drug-target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper, we propose a kind of drug-target interactions predictor adopting multi-scale discrete wavelet transform and network features (named as DAWN) in order to solve the DTIs prediction problem. We encode the drug molecule by a substructure fingerprint with a dictionary of substructure patterns...
August 16, 2017: International Journal of Molecular Sciences
Chi-Yi Tsai, Chih-Hung Huang
With the increasing popularity of RGB-depth (RGB-D) sensor, research on the use of RGB-D sensors to reconstruct three-dimensional (3D) indoor scenes has gained more and more attention. In this paper, an automatic point cloud registration algorithm is proposed to efficiently handle the task of 3D indoor scene reconstruction using pan-tilt platforms on a fixed position. The proposed algorithm aims to align multiple point clouds using extrinsic parameters of the RGB-D camera obtained from every preset pan-tilt control point...
August 15, 2017: Sensors
Zhixin Yan, Mao Ye, Liu Ren
Visual SLAM is one of the key technologies to align the virtual and real world together in Augmented Reality applications. RGBD dense Visual SLAM approaches have shown their advantages in robustness and accuracy in recent years. However, there are still several challenges such as the inconsistencies in RGBD measurements across multiple frames that could jeopardize the accuracy of both camera trajectory and scene reconstruction. In this paper, we propose a novel map representation called Probabilistic Surfel Map (PSM) for dense visual SLAM...
August 10, 2017: IEEE Transactions on Visualization and Computer Graphics
Li Zhou, Zhaohui Yang, Zongtan Zhou, Dewen Hu
Diffusion-based salient region detection has recently received intense research attention. In this paper, we present some effective improvements concerning two important aspects of diffusion-based methods: the construction of the diffusion matrix and the seed vector. First, we construct a 2-layer sparse graph, which is generated by connecting each node to its neighboring nodes and the most similar node that shares common boundaries with its neighboring nodes. Compared with the most frequently used 2-layer neighborhood graph, our graph not only effectively uses local spatial relationships, but also removes dissimilar redundant nodes...
August 11, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Shuo Chen, Jian Yang, Lei Luo, Yang Wei, Kaihua Zhang, Ying Tai
This paper develops a novel method to address the structural noise in samples for image classification. Recently, regression related classification methods have shown promising results when facing the pixel-wise noise. However, they become weak in coping with the structural noise due to ignoring of relationships between pixels of noise image. Meanwhile, most of them need to implement the iterative process for computing representation coefficients, which leads to the high time consumption. To overcome these problems, we exploit a latent pattern model called Low-Rank Latent Pattern Approximation (LLPA) to reconstruct the test image having structural noise...
August 10, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Nora Baka, Sieger Leenstra, Theo van Walsum
Localization of the correct vertebral level for surgical entry during lumbar hernia surgery is not straightforward. In this paper we develop and evaluate a solution using free-hand 2D ultrasound (US) imaging in the operation room (OR). Our system exploits the difference in spinous process shapes of the vertebrae. The spinous processes are pre-operatively outlined and labeled in a lateral lumbar X-ray of the patient. Then, in the OR the spinous processes are imaged with 2D sagittal US, and are automatically segmented and registered with the X-ray shapes...
August 10, 2017: IEEE Transactions on Medical Imaging
Hu Han, Anil K Jain, Shiguang Shan, Xilin Chen
Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image...
August 10, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Jaydeep De, Xiaowei Zhang, Feng Lin, Li Cheng
In this paper we consider the problem of graph-based transductive classification, and we are particularly interested in the directed graph scenario which is a natural form for many real world applications.Different from existing research efforts that either only deal with undirected graphs or circumvent directionality by means of symmetrization, we propose a novel random walk approach on directed graphs using absorbing Markov chains, which can be regarded as maximizing the accumulated expected number of visits from the unlabeled transient states...
August 11, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
Fernando Cervantes-Sanchez, Ivan Cruz-Aceves, Arturo Hernandez-Aguirre, Sergio Solorio-Meza, Teodoro Cordova-Fraga, Juan Gabriel Aviña-Cervantes
Segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis, since it can help cardiologists in diagnosing and monitoring vascular abnormalities. Due to the main disadvantages of the X-ray angiograms are the nonuniform illumination, and the weak contrast between blood vessels and image background, different vessel enhancement methods have been introduced. In this paper, a novel method for blood vessel enhancement based on Gabor filters tuned using the optimization strategy of Differential evolution (DE) is proposed...
August 5, 2017: Applied Radiation and Isotopes
Ilker Hacihaliloglu
Due to its real-time, non-radiation based three-dimensional (3D) imaging capabilities, ultrasound (US) has been incorporated into various orthopedic procedures. However, imaging artifacts, low signal-to-noise ratio (SNR) and bone boundaries appearing several mm in thickness make the analysis of US data difficult. This paper provides a review about the state-of-the-art bone segmentation and enhancement methods developed for two-dimensional (2D) and 3D US data. First, an overview for the appearance of bone surface response in B-mode data is presented...
June 2017: Technology
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