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https://www.readbyqxmd.com/read/28814023/representing-high-dimensional-data-to-intelligent-prostheses-and-other-wearable-assistive-robots-a-first-comparison-of-tile-coding-and-selective-kanerva-coding
#1
Jaden B Travnik, Patrick M Pilarski
Prosthetic devices have advanced in their capabilities and in the number and type of sensors included in their design. As the space of sensorimotor data available to a conventional or machine learning prosthetic control system increases in dimensionality and complexity, it becomes increasingly important that this data be represented in a useful and computationally efficient way. Well structured sensory data allows prosthetic control systems to make informed, appropriate control decisions. In this study, we explore the impact that increased sensorimotor information has on current machine learning prosthetic control approaches...
July 2017: IEEE ... International Conference on Rehabilitation Robotics: [proceedings]
https://www.readbyqxmd.com/read/28813643/multi-connection-pattern-analysis-decoding-the-representational-content-of-neural-communication
#2
Yuanning Li, R Mark Richardson, Avniel Singh Ghuman
The lack of multivariate methods for decoding the representational content of interregional neural communication has left it difficult to know what information is represented in distributed brain circuit interactions. Here we present Multi-Connection Pattern Analysis (MCPA), which works by learning mappings between the activity patterns of the populations as a factor of the information being processed. These maps are used to predict the activity from one neural population based on the activity from the other population...
August 13, 2017: NeuroImage
https://www.readbyqxmd.com/read/28809718/integration-of-semantic-and-episodic-memories
#3
Adrian Horzyk, Janusz A Starzyk, James Graham
This paper describes the integration of semantic and episodic memory (EM) models and the benefits of such integration. Semantic memory (SM) is used as a foundation of knowledge and concept learning, and is needed for the operation of any cognitive system. EM retains personal experiences stored based on their significance--it is supported by the SM, and in return, it supports SM operations. Integrated declarative memories are critical for cognitive system development, yet very little research has been done to develop their computational models...
August 11, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28809716/structured-weak-semantic-space-construction-for-visual-categorization
#4
Chunjie Zhang, Jian Cheng, Qi Tian
Visual features have been widely used for image representation and categorization. However, visual features are often inconsistent with human perception. Besides, constructing explicit semantic space is still an open problem. To alleviate these two problems, in this paper, we propose to construct structured weak semantic space for image representation. Exemplar classifier is first trained to separate each training image from other images for weak semantic space construction. However, each exemplar classifier separates one training image from other images, and it only has limited semantic separability...
August 11, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28809673/heterogeneous-face-attribute-estimation-a-deep-multi-task-learning-approach
#5
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
https://www.readbyqxmd.com/read/28808826/use-of-evidence-in-a-categorization-task-analytic-and-holistic-processing-modes
#6
Alberto Greco, Stefania Moretti
Category learning performance can be influenced by many contextual factors, but the effects of these factors are not the same for all learners. The present study suggests that these differences can be due to the different ways evidence is used, according to two main basic modalities of processing information, analytically or holistically. In order to test the impact of the information provided, an inductive rule-based task was designed, in which feature salience and comparison informativeness between examples of two categories were manipulated during the learning phases, by introducing and progressively reducing some perceptual biases...
August 14, 2017: Cognitive Processing
https://www.readbyqxmd.com/read/28807104/understanding-practitioner-professionalism-in-aboriginal-and-torres-strait-islander-health-lessons-from-student-and-registrar-placements-at-an-urban-aboriginal-and-torres-strait-islander-primary-healthcare-service
#7
Deborah A Askew, Vivian J Lyall, Shaun C Ewen, David Paul, Melissa Wheeler
Aboriginal and Torres Strait Islander peoples continue to be pathologised in medical curriculum, leaving graduates feeling unequipped to effectively work cross-culturally. These factors create barriers to culturally safe health care for Aboriginal and Torres Strait Islander peoples. In this pilot pre-post study, the learning experiences of seven medical students and four medical registrars undertaking clinical placements at an urban Aboriginal and Torres Strait Islander primary healthcare service in 2014 were followed...
August 15, 2017: Australian Journal of Primary Health
https://www.readbyqxmd.com/read/28804738/social-observation-task-in-a-linear-maze-for-rats
#8
Xiang Mou, Daoyun Ji
Animals often learn through observing their conspecifics. However, the mechanisms of them obtaining useful knowledge during observation are beginning to be understood. This protocol describes a novel social observation task to test the 'local enhancement theory', which proposes that presence of social subjects in an environment facilitates one's understanding of the environments. By combining behavior test and in vivo electrophysiological recording, we found that social observation can facilitate the observer's spatial representation of an unexplored environment...
July 5, 2017: Bio-protocol
https://www.readbyqxmd.com/read/28802770/efficacy-of-navigation-may-be-influenced-by-retrosplenial-cortex-mediated-learning-of-landmark-stability
#9
Stephen D Auger, Peter Zeidman, Eleanor A Maguire
Human beings differ considerably in their ability to orient and navigate within the environment, but it has been difficult to determine specific causes of these individual differences. Permanent, stable landmarks are thought to be crucial for building a mental representation of an environment. Poor, compared to good, navigators have been shown to have difficulty identifying permanent landmarks, with a concomitant reduction in functional MRI (fMRI) activity in the retrosplenial cortex. However, a clear association between navigation ability and the learning of permanent landmarks has not been established...
August 9, 2017: Neuropsychologia
https://www.readbyqxmd.com/read/28802103/where-you-are-affects-what-you-can-easily-imagines-environmental-geometry-elicits-sensorimotor-interference-in-remote-perspective-taking
#10
Bernhard E Riecke, Timothy P McNamara
Imagined perspective switches are notoriously difficult, a fact often ascribed to sensorimotor interference between one's to-be-imagined versus actual orientation. Here, we demonstrate similar interference effects, even if participants know they are in a remote environment with unknown spatial relation to the learning environment. Participants learned 15 target objects irregularly arranged in an office from one orientation (0°, 120°, or 240°). Participants were blindfolded and disoriented before being wheeled to a test room of similar geometry (exp...
August 9, 2017: Cognition
https://www.readbyqxmd.com/read/28800619/-what-is-relevant-in-a-text-document-an-interpretable-machine-learning-approach
#11
Leila Arras, Franziska Horn, Grégoire Montavon, Klaus-Robert Müller, Wojciech Samek
Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML) models have been trained to automatically map documents to these abstract concepts, allowing to annotate very large text collections, more than could be processed by a human in a lifetime. Besides predicting the text's category very accurately, it is also highly desirable to understand how and why the categorization process takes place. In this paper, we demonstrate that such understanding can be achieved by tracing the classification decision back to individual words using layer-wise relevance propagation (LRP), a recently developed technique for explaining predictions of complex non-linear classifiers...
2017: PloS One
https://www.readbyqxmd.com/read/28799130/near-set-based-mucin-segmentation-in-histopathology-images-for-detecting-mucinous-carcinoma
#12
Soma Banerjee, Monjoy Saha, Indu Arun, Bijan Basak, Sanjit Agarwal, Rosina Ahmed, Sanjoy Chatterjee, Lipi B Mahanta, Chandan Chakraborty
This paper introducesnear-set based segmentation method for extraction and quantification of mucin regions for detecting mucinouscarcinoma (MC which is a sub type of Invasive ductal carcinoma (IDC)). From histology point of view, the presence of mucin is one of the indicators for detection of this carcinoma. In order to detect MC, the proposed method majorly includes pre-processing by colour correction, colour transformation followed by near-set based segmentation and post-processing for delineating only mucin regions from the histological images at 40×...
August 10, 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28798957/holographic-deep-learning-for-rapid-optical-screening-of-anthrax-spores
#13
YoungJu Jo, Sangjin Park, JaeHwang Jung, Jonghee Yoon, Hosung Joo, Min-Hyeok Kim, Suk-Jo Kang, Myung Chul Choi, Sang Yup Lee, YongKeun Park
Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be used in realistic settings of biological warfare. We present an optical method for rapid and label-free screening of Bacillus anthracis spores through the synergistic application of holographic microscopy and deep learning. A deep convolutional neural network is designed to classify holographic images of unlabeled living cells...
August 2017: Science Advances
https://www.readbyqxmd.com/read/28798659/enhanced-data-representation-by-kernel-metric-learning-for-dementia-diagnosis
#14
David Cárdenas-Peña, Diego Collazos-Huertas, German Castellanos-Dominguez
Alzheimer's disease (AD) is the kind of dementia that affects the most people around the world. Therefore, an early identification supporting effective treatments is required to increase the life quality of a wide number of patients. Recently, computer-aided diagnosis tools for dementia using Magnetic Resonance Imaging scans have been successfully proposed to discriminate between patients with AD, mild cognitive impairment, and healthy controls. Most of the attention has been given to the clinical data, provided by initiatives as the ADNI, supporting reliable researches on intervention, prevention, and treatments of AD...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28797600/the-rat-retrosplenial-cortex-as-a-link-for-frontal-functions-a-lesion-analysis
#15
Anna L Powell, Andrew Nelson, Emma Hindley, Moira Davies, John P Aggleton, Seralynne D Vann
Cohorts of rats with excitotoxic retrosplenial cortex lesions were tested on four behavioural tasks sensitive to dysfunctions in prelimbic cortex, anterior cingulate cortex, or both. In this way the study tested whether retrosplenial cortex has nonspatial functions that reflect its anatomical interactions with these frontal cortical areas. In Experiment 1, retrosplenial cortex lesions had no apparent effect on a set-shifting digging task that taxed intradimensional and extradimensional attention, as well as reversal learning...
August 7, 2017: Behavioural Brain Research
https://www.readbyqxmd.com/read/28797034/unsupervised-learning-of-temporal-features-for-word-categorization-in-a-spiking-neural-network-model-of-the-auditory-brain
#16
Irina Higgins, Simon Stringer, Jan Schnupp
The nature of the code used in the auditory cortex to represent complex auditory stimuli, such as naturally spoken words, remains a matter of debate. Here we argue that such representations are encoded by stable spatio-temporal patterns of firing within cell assemblies known as polychronous groups, or PGs. We develop a physiologically grounded, unsupervised spiking neural network model of the auditory brain with local, biologically realistic, spike-time dependent plasticity (STDP) learning, and show that the plastic cortical layers of the network develop PGs which convey substantially more information about the speaker independent identity of two naturally spoken word stimuli than does rate encoding that ignores the precise spike timings...
2017: PloS One
https://www.readbyqxmd.com/read/28796619/unsupervised-t-distributed-video-hashing-and-its-deep-hashing-extension
#17
Yanbin Hao, Tingting Mu, John Y Goulermas, Jianguo Jiang, Richang Hong, Meng Wang
In this work, a novel unsupervised hashing algorithm, referred to as t-USMVH, and its extension to unsupervised deep hashing, referred to as t-UDH, are proposed to support large-scale video-to-video retrieval. To improve robustness of the unsupervised learning, t-USMVH combines multiple types of feature representations and effectively fuses them by examining a continuous relevance score based on a Gaussian estimation over pairwise distances, and also a discrete neighbor score based on the cardinality of reciprocal neighbors...
August 7, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28796611/simultaneous-local-binary-feature-learning-and-encoding-for-homogeneous-and-heterogeneous-face-recognition
#18
Jiwen Lu, Venice Erin Liong, Jie Zhou
In this paper, we propose a simultaneous local binary feature learning and encoding (SLBFLE) approach for both homogeneous and heterogeneous face recognition. Unlike existing hand-crafted face descriptors such as local binary pattern (LBP) and Gabor features which usually require strong prior knowledge, our SLBFLE is an unsupervised feature learning approach which automatically learns face representation from raw pixels. Unlike existing binary face descriptors such as the LBP, discriminant face descriptor (DFD), and compact binary face descriptor (CBFD) which use a two-stage feature extraction procedure, our SLBFLE jointly learns binary codes and the codebook for local face patches so that discriminative information from raw pixels from face images of different identities can be obtained by using a one-stage feature learning and encoding procedure...
August 9, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28796604/dual-temporal-and-spatial-sparse-representation-for-inferring-group-wise-brain-networks-from-resting-state-fmri-dataset
#19
Junhui Gong, Xiaoyan Liu, Tianming Liu, Jiansong Zhou, Gang Sun, Juanxiu Tian
Recently, sparse representation has been successfully used to identify brain networks from task-based fMRI dataset. However, when using the strategy to analyze resting-state fMRI dataset, it is still a challenge to automatically infer the group-wise brain networks under consideration of group commonalities and subject-specific characteristics. In the paper, a novel method based on dual temporal and spatial sparse representation (DTSSR) is proposed to meet this challenge. Firstly, the brain functional networks with subject-specific characteristics are obtained via sparse representation with online dictionary learning for the fMRI time series (temporal domain) of each subject...
August 9, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28794465/the-mechanical-representation-of-temporal-delays
#20
Raz Leib, Amir Karniel, Ferdinando A Mussa-Ivaldi
When we knock on a door, we perceive the impact as a collection of simultaneous events, combining sound, sight, and tactile sensation. In reality, information from different modalities but from a single source is flowing inside the brain along different pathways, reaching processing centers at different times. Therefore, interpreting different sensory modalities which seem to occur simultaneously requires information processing that accounts for these different delays. As in a computer-based robotic system, does the brain use some explicit estimation of the time delay, to realign the sensory flows? Or does it compensate for temporal delays by representing them as changes in the body/environment mechanics? Using delayed-state or an approximation for delayed-state manipulations between visual and proprioceptive feedback during a tracking task, we show that tracking errors, grip forces, and learning curves are consistent with predictions of a representation that is based on approximation for delay, refuting an explicit delayed-state representation...
August 9, 2017: Scientific Reports
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