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https://www.readbyqxmd.com/read/28436874/track-everything-limiting-prior-knowledge-in-online-multi-object-recognition
#1
Sebastien C Wong, Victor Stamatescu, Adam Gatt, David Kearney, Ivan Lee, Mark D McDonnell
This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fastlearning image classifier that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm...
April 24, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28435902/emergency-medical-service-personnel-need-to-improve-knowledge-and-attitude-regarding-prehospital-sepsis-care
#2
Joongmin Park, Sung Yeon Hwang, Tae Gun Shin, Ik Joon Jo, Hee Yoon, Tae Rim Lee, Won Chul Cha, Min Seob Sim
OBJECTIVE: We aimed to evaluate the knowledge and attitudes of emergency medical service (EMS) personnel pertaining to sepsis. We also compared EMS personnel's knowledge of sepsis and their intention to engage in prehospital sepsis management. METHODS: The survey was conducted during education conferences for EMS personnel in December 2013 and January 2015 in Seoul, Korea. The questionnaire composed of 10 questions relevant to sepsis, was distributed on-scene, and was retrieved by investigators after the conference...
March 2017: Clinical and Experimental Emergency Medicine
https://www.readbyqxmd.com/read/28410105/dynamic-textures-modeling-via-joint-video-dictionary-learning
#3
Xian Wei, Yuanxiang Li, Hao Shen, Fang Chen, Martin Kleinsteuber, Zhongfeng Wang
Video representation is an important and challenging task in the computer vision community. In this paper, we consider the problem of modeling and classifying video sequences of dynamic scenes which could be modeled in a dynamic textures (DT) framework. At first, we assume that image frames of a moving scene can be modeled as a Markov random process. We propose a sparse coding framework, named joint video dictionary learning (JVDL), to model a video adaptively. By treating the sparse coefficients of image frames over a learned dictionary as the underlying "states", we learn an efficient and robust linear transition matrix between two adjacent frames of sparse events in time series...
April 6, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28401988/a-rapid-nuclear-staining-test-using-cationic-dyes-contributes-to-efficient-str-analysis-of-telogen-hair-roots
#4
So-Yeon Lee, Eun-Ju Ha, Seung-Kyun Woo, So-Min Lee, Kyung-Hee Lim, Yong-Bin Eom
Telogen hairs presented in the crime scene are commonly encountered as trace evidence. However, short tandem repeat (STR) profiling of the hairs currently have low and limited use due to poor success rate. To increase the success rate of STR profiling of telogen hairs, we developed a rapid and cost-effective method to estimate the number of nuclei in the hair roots. Five cationic dyes, Methyl green (MG), Harris hematoxylin (HH), Methylene blue (MB), Toluidine blue (TB) and Safranin O (SO) were evaluated in this study...
April 12, 2017: Electrophoresis
https://www.readbyqxmd.com/read/28399149/sequential-monte-carlo-guided-ensemble-tracking
#5
Yuru Wang, Qiaoyuan Liu, Longkui Jiang, Minghao Yin, Shengsheng Wang
A great deal of robustness is allowed when visual tracking is considered as a classification problem. This paper combines a finite number of weak classifiers in a SMC framework as a strong classifier. The time-varying ensemble parameters (confidence of weak classifiers) are regarded as sequential arriving states and their posterior distribution is estimated in a Bayesian manner. Therefore, both the adaptiveness and stability are kept for the ensemble classification in handling scene changes and target deformation...
2017: PloS One
https://www.readbyqxmd.com/read/28387587/multiple-object-tracking-as-a-tool-for-parametrically-modulating-memory-reactivation
#6
Jordan Poppenk, Ken A Norman
Converging evidence supports the "nonmonotonic plasticity" hypothesis that, although complete retrieval may strengthen memories, partial retrieval weakens them. Yet, the classic experimental paradigms used to study effects of partial retrieval are not ideally suited to doing so, because they lack the parametric control needed to ensure that the memory is activated to the appropriate degree (i.e., that there is some retrieval but not enough to cause memory strengthening). Here, we present a novel procedure designed to accommodate this need...
April 7, 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28343000/evidence-for-similar-patterns-of-neural-activity-elicted-by-picture-and-word-based-representations-of-natural-scenes
#7
Manoj Kumar, Kara D Federmeier, Li Fei-Fei, Diane M Beck
A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g...
March 22, 2017: NeuroImage
https://www.readbyqxmd.com/read/28336425/characterizing-object-and-position-dependent-response-profiles-to-uni-and-bilateral-stimulus-configurations-in-human-higher-visual-cortex-a-7t-fmri-study
#8
Joel Reithler, Judith C Peters, Rainer Goebel
Visual scenes are initially processed via segregated neural pathways dedicated to either of the two visual hemifields. Although higher-order visual areas are generally believed to utilize invariant object representations (abstracted away from features such as stimulus position), recent findings suggest they retain more spatial information than previously thought. Here, we assessed the nature of such higher-order object representations in human cortex using high-resolution fMRI at 7T, supported by corroborative 3T data...
March 21, 2017: NeuroImage
https://www.readbyqxmd.com/read/28333644/random-forest-classifier-for-zero-shot-learning-based-on-relative-attribute
#9
Yuhu Cheng, Xue Qiao, Xuesong Wang, Qiang Yu
For the zero-shot image classification with relative attributes (RAs), the traditional method requires that not only all seen and unseen images obey Gaussian distribution, but also the classifications on testing samples are made by maximum likelihood estimation. We therefore propose a novel zero-shot image classifier called random forest based on relative attribute. First, based on the ordered and unordered pairs of images from the seen classes, the idea of ranking support vector machine is used to learn ranking functions for attributes...
March 21, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28316563/a-saccade-based-framework-for-real-time-motion-segmentation-using-event-based-vision-sensors
#10
Abhishek Mishra, Rohan Ghosh, Jose C Principe, Nitish V Thakor, Sunil L Kukreja
Motion segmentation is a critical pre-processing step for autonomous robotic systems to facilitate tracking of moving objects in cluttered environments. Event based sensors are low power analog devices that represent a scene by means of asynchronous information updates of only the dynamic details at high temporal resolution and, hence, require significantly less calculations. However, motion segmentation using spatiotemporal data is a challenging task due to data asynchrony. Prior approaches for object tracking using neuromorphic sensors perform well while the sensor is static or a known model of the object to be followed is available...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28294963/voxel-based-neighborhood-for-spatial-shape-pattern-classification-of-lidar-point-clouds-with-supervised-learning
#11
Victoria Plaza-Leiva, Jose Antonio Gomez-Ruiz, Anthony Mandow, Alfonso García-Cerezo
Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself...
March 15, 2017: Sensors
https://www.readbyqxmd.com/read/28268456/emotion-classification-using-single-channel-scalp-eeg-recording
#12
Amir Jalilifard, Ednaldo Brigante Pizzolato, Md Kafiul Islam
Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perceived as fear or threatening scene. Recent studies showed that neural oscillations' patterns in Theta, Alpha, Beta and Gamma sub-bands play a main role in brain's emotional processing. The main goal of this study is to classify two different emotional states by means of EEG data recorded through a single-electrode EEG headset. Nineteen young subjects participated in an EEG experiment while watching a video clip that evoked three emotional states: neutral, relaxation and scary...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28241028/deploying-a-quantum-annealing-processor-to-detect-tree-cover-in-aerial-imagery-of-california
#13
Edward Boyda, Saikat Basu, Sangram Ganguly, Andrew Michaelis, Supratik Mukhopadhyay, Ramakrishna R Nemani
Quantum annealing is an experimental and potentially breakthrough computational technology for handling hard optimization problems, including problems of computer vision. We present a case study in training a production-scale classifier of tree cover in remote sensing imagery, using early-generation quantum annealing hardware built by D-wave Systems, Inc. Beginning within a known boosting framework, we train decision stumps on texture features and vegetation indices extracted from four-band, one-meter-resolution aerial imagery from the state of California...
2017: PloS One
https://www.readbyqxmd.com/read/28226629/emotion-classification-using-single-channel-scalp-eeg-recording
#14
Amir Jalilifard, Ednaldo Brigante Pizzolato, Md Kafiul Islam, Amir Jalilifard, Ednaldo Brigante Pizzolato, Md Kafiul Islam, Ednaldo Brigante Pizzolato, Amir Jalilifard, Md Kafiul Islam
Several studies have found evidence for corticolimbic Theta electroencephalographic (EEG) oscillation in the neural processing of visual stimuli perceived as fear or threatening scene. Recent studies showed that neural oscillations' patterns in Theta, Alpha, Beta and Gamma sub-bands play a main role in brain's emotional processing. The main goal of this study is to classify two different emotional states by means of EEG data recorded through a single-electrode EEG headset. Nineteen young subjects participated in an EEG experiment while watching a video clip that evoked three emotional states: neutral, relaxation and scary...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28221995/deep-cascade-cascading-3d-deep-neural-networks-for-fast-anomaly-detection-and-localization-in-crowded-scenes
#15
Mohammad Sabokrou, Mohsen Fayyaz, Mahmood Fathy, Reinhard Klette
This paper proposes a fast and reliable method for anomaly detection and localization in video data showing crowded scenes. Time-efficient anomaly localization is an ongoing challenge and subject of this paper. We propose a cubicpatch- based method, characterised by a cascade of classifiers, which makes use of an advanced feature-learning approach. Our cascade of classifiers has two main stages. First, a light but deep 3D auto-encoder is used for early identification of "many" normal cubic patches. This deep network operates on small cubic patches as being the first stage, before carefully resizing remaining candidates of interest, and evaluating those at the second stage using a more complex and deeper 3D convolutional neural network (CNN)...
February 17, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
https://www.readbyqxmd.com/read/28220910/chemical-incidents-resulted-in-hazardous-substances-releases-in-the-context-of-human-health-hazards
#16
Anna Pałaszewska-Tkacz, Sławomir Czerczak, Katarzyna Konieczko
OBJECTIVES: The research purpose was to analyze data concerning chemical incidents in Poland collected in 1999-2009 in terms of health hazards. MATERIAL AND METHODS: The data was obtained, using multimodal information technology (IT) system, from chemical incidents reports prepared by rescuers at the scene. The final analysis covered sudden events associated with uncontrolled release of hazardous chemical substances or mixtures, which may potentially lead to human exposure...
February 21, 2017: International Journal of Occupational Medicine and Environmental Health
https://www.readbyqxmd.com/read/28215821/holistic-versus-feature-based-binding-in-the-medial-temporal-lobe
#17
Rebecca N van den Honert, Gregory McCarthy, Marcia K Johnson
A central question for cognitive neuroscience is how feature-combinations that give rise to episodic/source memories are encoded in the brain. Although there is much evidence that the hippocampus (HIP) is involved in feature binding, and some evidence that other brain regions are as well, there is relatively little evidence about the nature of the resulting representations in different brain regions. We used multivoxel pattern analysis (MVPA) to investigate how feature combinations might be represented, contrasting two possibilities, feature-based versus holistic...
January 23, 2017: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/28213572/impact-of-expanding-the-prehospital-stroke-bypass-time-window-in-a-large-geographic-region
#18
Ian G Stiell, Catherine M Clement, Kristy Campbell, Mukul Sharma, Doug Socha, Marco L A Sivilotti, Albert Jin, Jeffrey J Perry, Jim Lumsden, Cally Martin, Mark Froats, Richard Dionne, John Trickett
BACKGROUND AND PURPOSE: The Ontario Acute Stroke Medical Redirect Paramedic Protocol (ASMRPP) was revised to allow paramedics to bypass to designated stroke centers if total transport time would be <2 hours and total time from symptom onset <3.5 hours. We sought to evaluate the impact and safety of implementing the Revised ASMRPP. METHODS: We conducted a 12-month implementation study involving prehospital patients presenting with possible stroke symptoms. A total of 1317 basic and advanced life support paramedics, of 9 land services in 10 rural counties and 5 cities, used the Revised ASMRPP to take appropriate patients directly to 6 designated stroke centers...
February 17, 2017: Stroke; a Journal of Cerebral Circulation
https://www.readbyqxmd.com/read/28184211/disrupted-saccade-control-in-chronic-cerebral-injury-upper-motor-neuron-like-disinhibition-in-the-ocular-motor-system
#19
John-Ross Rizzo, Todd E Hudson, Andrew Abdou, Yvonne W Lui, Janet C Rucker, Preeti Raghavan, Michael S Landy
Saccades rapidly direct the line of sight to targets of interest to make use of the high acuity foveal region of the retina. These fast eye movements are instrumental for scanning visual scenes, foveating targets, and, ultimately, serve to guide manual motor control, including eye-hand coordination. Cerebral injury has long been known to impair ocular motor control. Recently, it has been suggested that alterations in control may be useful as a marker for recovery. We measured eye movement control in a saccade task in subjects with chronic middle cerebral artery stroke with both cortical and substantial basal ganglia involvement and in healthy controls...
2017: Frontiers in Neurology
https://www.readbyqxmd.com/read/28113809/text-attentional-convolutional-neural-networks-for-scene-text-detection
#20
Tong He, Weilin Huang, Yu Qiao, Jian Yao
Recent deep learning models have demonstrated strong capabilities for classifying text and non-text components in natural images. They extract a high-level feature computed globally from a whole image component (patch), where the cluttered background information may dominate true text features in the deep representation. This leads to less discriminative power and poorer robustness. In this work, we present a new system for scene text detection by proposing a novel Text-Attentional Convolutional Neural Network (Text-CNN) that particularly focuses on extracting text-related regions and features from the image components...
March 28, 2016: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
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