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https://www.readbyqxmd.com/read/28549351/contextual-cueing-in-3d-visual-search-depends-on-representations-in-planar-not-depth-defined-space
#1
Xuelian Zang, Zhuanghua Shi, Hermann J Müller, Markus Conci
Learning of spatial inter-item associations can speed up visual search in everyday life, an effect referred to as contextual cueing (Chun & Jiang, 1998). Whereas previous studies investigated contextual cueing primarily using 2D layouts, the current study examined how 3D depth influences contextual learning in visual search. In two experiments, the search items were presented evenly distributed across front and back planes in an initial training session. In the subsequent test session, the search items were either swapped between the front and back planes (Experiment 1) or between the left and right halves (Experiment 2) of the displays...
May 1, 2017: Journal of Vision
https://www.readbyqxmd.com/read/28547011/the-effect-of-visual-variability-on-the-learning-of-academic-concepts
#2
Ashley Bourgoyne, Mary Alt
Purpose: The purpose of this study was to identify effects of variability of visual input on development of conceptual representations of academic concepts for college-age students with normal language (NL) and those with language-learning disabilities (LLD). Method: Students with NL (n = 11) and LLD (n = 11) participated in a computer-based training for introductory biology course concepts. Participants were trained on half the concepts under a low-variability condition and half under a high-variability condition...
May 26, 2017: Journal of Speech, Language, and Hearing Research: JSLHR
https://www.readbyqxmd.com/read/28545630/the-role-of-motor-imagery-in-learning-via-instructions
#3
Marijke Theeuwes, Baptist Liefooghe, Maarten De Schryver, Jan De Houwer
Learning via instructions and learning through physical practice are complementary pathways to obtain skilled performance. Whereas an initial task representation can be formed on the basis of instructions, physically practicing novel instructions leads to a shift in processing mode from controlled processing toward more automatic processing. This shift in processing mode is supposedly caused by the formation of a pragmatic task representation, which includes task parameters needed to attain skilled task execution...
May 23, 2017: Acta Psychologica
https://www.readbyqxmd.com/read/28545431/structured-feedback-on-students-concept-maps-the-proverbial-path-to-learning
#4
Conran Joseph, David Conradsson, Lena Nilsson Wikmar, Michael Rowe
BACKGROUND: Good conceptual knowledge is an essential requirement for health professions students, in that they are required to apply concepts learned in the classroom to a variety of different contexts. However, the use of traditional methods of assessment limits the educator's ability to correct students' conceptual knowledge prior to altering the educational context. Concept mapping (CM) is an educational tool for evaluating conceptual knowledge, but little is known about its use in facilitating the development of richer knowledge frameworks...
May 25, 2017: BMC Medical Education
https://www.readbyqxmd.com/read/28542234/robust-auto-weighted-multi-view-subspace-clustering-with-common-subspace-representation-matrix
#5
Wenzhang Zhuge, Chenping Hou, Yuanyuan Jiao, Jia Yue, Hong Tao, Dongyun Yi
In many computer vision and machine learning applications, the data sets distribute on certain low-dimensional subspaces. Subspace clustering is a powerful technology to find the underlying subspaces and cluster data points correctly. However, traditional subspace clustering methods can only be applied on data from one source, and how to extend these methods and enable the extensions to combine information from various data sources has become a hot area of research. Previous multi-view subspace methods aim to learn multiple subspace representation matrices simultaneously and these learning task for different views are treated equally...
2017: PloS One
https://www.readbyqxmd.com/read/28541900/simultaneous-semi-coupled-dictionary-learning-for-matching-in-canonical-space
#6
Nilotpal Das, Devraj Mandal, Soma Biswas
Cross-modal recognition and matching with privileged information are important challenging problems in the field of computer vision. The cross-modal scenario deals with matching across different modalities and needs to take care of the large variations present across and within each modality. The privileged information scenario deals with the situation that all the information available during training may not be available during the testing stage and hence algorithms need to leverage the extra information from the training stage itself...
May 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28541202/linear-support-tensor-machine-with-lsk-channels-pedestrian-detection-in-thermal-infrared-images
#7
Sujoy Kumar Biswas, Peyman Milanfar
Pedestrian detection in thermal infrared images poses unique challenges because of the low resolution and noisy nature of the image. Here we propose a mid-level attribute in the form of the multidimensional template, or tensor, using Local Steering Kernel (LSK) as low-level descriptors for detecting pedestrians in far infrared images. LSK is specifically designed to deal with intrinsic image noise and pixel level uncertainty by capturing local image geometry succinctly instead of collecting local orientation statistics (e...
May 18, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28541201/palmprint-recognition-based-on-complete-direction-representation
#8
Wei Jia, Bob Zhang, Jingting Lu, Yihai Zhu, Yang Zhao, Wangmeng Zuo, Haibin Ling
Direction information serves as one of the most important features for palmprint recognition. In the past decade, many effective direction representation (DR)-based methods have been proposed and achieved promising recognition performance. However, due to an incomplete understanding for DR, these methods only extract DR in one direction level and one scale. Hence, they did not fully utilized all potentials of DR. In addition, most researchers only focused on the DR extraction in spatial coding domain, and rarely considered the methods in frequency domain...
May 18, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28541200/label-information-guided-graph-construction-for-semi-supervised-learning
#9
Liansheng Zhuang, Zihan Zhou, Shenghua Gao, Jingwen Yin, Zhouchen Lin, Yi Ma
In the literature, most existing graph-based semi- supervised learning (SSL) methods only use the label information of observed samples in the label propagation stage, while ignoring such valuable information when learning the graph. In this paper, we argue that it is beneficial to consider the label information in the graph learning stage. Specifically, by enforcing the weight of edges between labeled samples of different classes to be zero, we explicitly incorporate the label information into the state-of-the-art graph learning methods, such as the Low-Rank Representation (LRR), and propose a novel semi-supervised graph learning method called Semi-Supervised Low-Rank Representation (SSLRR)...
May 18, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28539910/the-role-of-emotional-landmarks-on-topographical-memory
#10
Massimiliano Palmiero, Laura Piccardi
The investigation of the role of emotional landmarks on human navigation has been almost totally neglected in psychological research. Therefore, the extent to which positive and negative emotional landmarks affect topographical memory as compared to neutral emotional landmark was explored. Positive, negative and neutral affect-laden images were selected as landmarks from the International Affective Picture System (IAPS) Inventory. The Walking Corsi test (WalCT) was used in order to test the landmark-based topographical memory...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28539425/perceptual-competition-promotes-suppression-of-reward-salience-in-behavioral-selection-and-neural-representation
#11
Mengyuan Gong, Ke Jia, Sheng Li
Visual attentional selection is influenced by the value of objects. Previous studies have demonstrated that reward-associated items lead to rapid distraction and associated behavioral costs, which are difficult to override with top-down control. However, it has not been determined whether a perceptually competitive environment could render the reward-driven distraction more susceptible to top-down suppression. Here, we trained both genders of human subjects to associate two orientations with high and low magnitudes of reward...
May 24, 2017: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28537779/simulation-model-for-laparoscopic-foregut-surgery-the-university-of-north-carolina-foregut-model
#12
Francisco Schlottmann, Neal S Murty, Marco G Patti
BACKGROUND: A significant gap presently exists between box-lap and virtual-reality simulators and live surgery. Live animal and cadaver use has significant downsides. We have developed a high fidelity, real tissue simulator that allows training in laparoscopic foregut operations. METHODS: Our foregut surgery model is based on porcine tissue blocks that include lungs, heart, aorta, esophagus, diaphragm, stomach, duodenum, liver, and spleen. The tissue block is mounted in a human mannequin and perfused with artificial blood...
May 24, 2017: Journal of Laparoendoscopic & Advanced Surgical Techniques. Part A
https://www.readbyqxmd.com/read/28537007/from-anticipation-to-integration-the-role-of-integrated-action-effects-in-building-sensorimotor-contingencies
#13
Thomas Camus, Bernhard Hommel, Lionel Brunel, Thibaut Brouillet
Ideomotor approaches to action control have provided evidence that the activation of an anticipatory image of previously learned action-effects plays a decisive role in action selection. This study sought for converging evidence by combining three previous experimental paradigms: the response-effect compatibility protocol introduced by Kunde (Journal of Experimental Psychology: Human Perception and Performance, 27(2), 387-394, 2001), the acquisition-test paradigm developed by Elsner and Hommel (Journal of Experimental Psychology: Human Perception and Performance, 27(1), 229, 2001), and the object-action compatibility manipulation of Tucker and Ellis (Visual Cognition, 8(6), 769-800, 2001)...
May 23, 2017: Psychonomic Bulletin & Review
https://www.readbyqxmd.com/read/28535192/learning-through-chain-event-graphs-the-role-of-maternal-factors-in-childhood-type-i-diabetes
#14
Claire Keeble, Peter Adam Thwaites, Paul David Baxter, Stuart Barber Pgclthe, Roger Charles Parslow, Graham Richard Law
Chain event graphs are a graphical representation of a statistical model derived from event trees, previously applied to cohort studies but not to case-control studies. We apply the chain event graph framework to a Yorkshire case-control study of childhood type I diabetes, to examine four exposure variables associated with the mother, three of which are fully observed (her school-leaving-age, amniocenteses during pregnancy and delivery type) and one with missing values (her rhesus factor), while incorporating previous type I diabetes knowledge...
May 23, 2017: American Journal of Epidemiology
https://www.readbyqxmd.com/read/28534802/organ-location-determination-and-contour-sparse-representation-for-multi-organ-segmentation
#15
Siqi Li, Huiyan Jiang, Yu-Dong Yao, Benqiang Yang
Organ segmentation on computed tomography (CT) images is of great importance in medical diagnoses and treatment. This paper proposes organ location determination and contour sparse representation methods (OLD-CSR) for multiorgan segmentation (liver, kidney, and spleen) on abdomen CT images using an extreme learning machine (ELM) classifier. First, a location determination method is designed to obtain location information of each organ, which is used for coarse segmentation. Second, for coarse-to-fine segmentation, a contour gradient and rate change based feature point extraction method is proposed...
May 17, 2017: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28534788/rankmap-a-framework-for-distributed-learning-from-dense-data-sets
#16
Azalia Mirhoseini, Eva L Dyer, Ebrahim M Songhori, Richard Baraniuk, Farinaz Koushanfar
This paper introduces RankMap, a platform-aware end-to-end framework for efficient execution of a broad class of iterative learning algorithms for massive and dense data sets. Our framework exploits data structure to scalably factorize it into an ensemble of lower rank subspaces. The factorization creates sparse low-dimensional representations of the data, a property which is leveraged to devise effective mapping and scheduling of iterative learning algorithms on the distributed computing machines. We provide two APIs, one matrix-based and one graph-based, which facilitate automated adoption of the framework for performing several contemporary learning applications...
May 17, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28534775/learning-rotation-invariant-local-binary-descriptor
#17
Yueqi Duan, Jiwen Lu, Jianjiang Feng, Jie Zhou
In this paper, we propose a rotation-invariant local binary descriptor (RI-LBD) learning method for visual recognition. Compared with hand-crafted local binary descriptors such as LBP and its variants which require strong prior knowledge, local binary feature learning methods are more efficient and dataadaptive. Unlike existing learning-based local binary descriptors such as compact binary face descriptor (CBFD) and simultaneous local binary feature learning and encoding (SLBFLE) which are susceptible to rotations, our RI-LBD first categorizes each local patch into a rotational binary pattern (RBP), and then jointly learns the orientation for each pattern and the projection matrix to obtain rotation-invariant local binary descriptors...
May 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28534773/sparsity-based-color-image-super-resolution-via-exploiting-cross-channel-constraints
#18
Hojjat Mousavi, Vishal Monga
Sparsity constrained single image super-resolution (SR) has been of much recent interest. A typical approach involves sparsely representing patches in a low-resolution (LR) input image via a dictionary of example LR patches, and then using the coefficients of this representation to generate the highresolution (HR) output via an analogous HR dictionary. However, most existing sparse representation methods for super resolution focus on the luminance channel information and do not capture interactions between color channels...
May 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28530717/sparse-coding-with-memristor-networks
#19
Patrick M Sheridan, Fuxi Cai, Chao Du, Wen Ma, Zhengya Zhang, Wei D Lu
Sparse representation of information provides a powerful means to perform feature extraction on high-dimensional data and is of broad interest for applications in signal processing, computer vision, object recognition and neurobiology. Sparse coding is also believed to be a key mechanism by which biological neural systems can efficiently process a large amount of complex sensory data while consuming very little power. Here, we report the experimental implementation of sparse coding algorithms in a bio-inspired approach using a 32 × 32 crossbar array of analog memristors...
May 22, 2017: Nature Nanotechnology
https://www.readbyqxmd.com/read/28529758/noise-aware-dictionary-learning-based-sparse-representation-framework-for-detection-and-removal-of-single-and-combined-noises-from-ecg-signal
#20
Udit Satija, Barathram Ramkumar, M Sabarimalai Manikandan
Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction...
February 2017: Healthcare Technology Letters
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