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Vision training

Talha Iqbal, Hazrat Ali
Deep learning algorithms produces state-of-the-art results for different machine learning and computer vision tasks. To perform well on a given task, these algorithms require large dataset for training. However, deep learning algorithms lack generalization and suffer from over-fitting whenever trained on small dataset, especially when one is dealing with medical images. For supervised image analysis in medical imaging, having image data along with their corresponding annotated ground-truths is costly as well as time consuming since annotations of the data is done by medical experts manually...
October 12, 2018: Journal of Medical Systems
Dmitry Krotov, John Hopfield
Deep neural networks (DNNs) trained in a supervised way suffer from two known problems. First, the minima of the objective function used in learning correspond to data points (also known as rubbish examples or fooling images) that lack semantic similarity with the training data. Second, a clean input can be changed by a small, and often imperceptible for human vision, perturbation so that the resulting deformed input is misclassified by the network. These findings emphasize the differences between the ways DNNs and humans classify patterns and raise a question of designing learning algorithms that more accurately mimic human perception compared to the existing methods...
October 12, 2018: Neural Computation
David Albala, Michael S Manak, Jonathan S Varsanik, Hani H Rashid, Vladimir Mouraviev, Stephen M Zappala, Ene Ette, Naveen Kella, Kimberly M Rieger-Christ, Grannum R Sant, Ashok C Chander
OBJECTIVE: To examine the ability of a novel live primary-cell phenotypic (LPCP) test to predict post-surgical adverse pathology (AP) features and risk stratify patients based on surgical adverse pathology features in a blinded study utilizing radical prostatectomy (RP) surgical specimens. SUBJECTS: 251 men undergoing RP were enrolled in a prospective, multi-center (10), proof-of-concept study in the United States. Fresh prostate samples were taken from known areas of cancer in the operating room immediately after RP...
October 9, 2018: Urology
Mary Jayne Kennedy
The field of personalized medicine affords multiple opportunities to pharmacists, and pharmacists have specific knowledge, skills and abilities that make them uniquely suited to advance the use of personalized medicine as a clinical tool. The pharmacy profession as a whole, however, has been slow to embrace the concept of clinical pharmacogenetics and is now facing a critical juncture that can potentially redefine the professional identity of the pharmacist. Before practice transformation can occur, however, it is important for our profession to ask and fully explore the following question: Are pharmacists ready for the challenge of personalized medicine? When assessing the readiness of pharmacy for personalized medicine, one must consider factors that are specific to the individual pharmacist as well as systematic considerations that allow pharmacists to successfully integrate personalized medicine into their individual practice area...
2018: Integrated Pharmacy Research and Practice
Cristina Calvo, Talía Sainz, Pilar Codoñer-Franch, Begoña Santiago, M Luz García-García, César García Vera, M Angeles Muñoz-Fernandez, Antonio Pérez-Martínez, Irene Rivero, Cristina Fernandez Pérez, Asunción Mejías, Federico Martinón-Torres, Fernando Cabañas
Research is the cornerstone of medical progress. Paediatric research has its own nuances and represents an additional challenge due to the intrinsic characteristics of the paediatric population compared with adults. Despite the tremendous importance of childhood health and its impact during adulthood, society is still not convinced about the importance of conducting research in paediatrics. This also applies to paediatricians themselves, who think about research as a discipline that does not directly involve them...
October 8, 2018: Anales de Pediatría: Publicación Oficial de la Asociación Española de Pediatría (A.E.P.)
Kenshiro Nishida, Kazuhiro Hotta
In recent years, finding the cause of pathogenesis is expected by observing the cell images. In this paper, we propose a cell particle detection method in cell images. However, there are mainly two kinds of problems in particle detection in cell image. The first is the different properties between cell images and standard images used in computer vision researches. Edges of cell particles are ambiguous, and overlaps between cell particles are often occurred in dense regions. It is difficult to detect cell particles by simple detection method using a binary classifier...
2018: PloS One
Matthew S Davenport, N Reed Dunnick
Leadership is increasingly recognized as a distinct set of trainable skills that are different from the skills of management. Dedicated attention to these skills by future leaders and the people who hire them is necessary to stem the tide of failed leadership that continues to remain all too common. Effective leaders prioritize others over self and are skilled communicators. They integrate information from disparate parties, encourage collaborative engagement, create a sense of urgency, and set the organizational vision...
October 2018: Radiographics: a Review Publication of the Radiological Society of North America, Inc
Salim Jabnoun, Rihab Borji, Sonia Sahli
In Parkour activity, the aim is to move from one place to another as quickly and efficiently as possible by running, climbing, swinging, vaulting, rolling, crawling and jumping on tiny obstacles … . Performing these actions places a great demand on the postural control system. The purpose of the present study was to investigate postural control of Parkour practitioners - called Traceurs - compared to recreationally active (RA) subjects in different postural conditions after manipulating the visual and/or proprioceptive sensory inputs...
October 10, 2018: European Journal of Sport Science
Yan Yan, Yuxing Mao, Bo Li
LiDAR-based or RGB-D-based object detection is used in numerous applications, ranging from autonomous driving to robot vision. Voxel-based 3D convolutional networks have been used for some time to enhance the retention of information when processing point cloud LiDAR data. However, problems remain, including a slow inference speed and low orientation estimation performance. We therefore investigate an improved sparse convolution method for such networks, which significantly increases the speed of both training and inference...
October 6, 2018: Sensors
Rebekka Hoffmann, Vigdís Vala Valgeirsdóttir, Ómar I Jóhannesson, Runar Unnthorsson, Árni Kristjánsson
Vibrotactile displays can compensate for the loss of sensory function of people with permanent or temporary deficiencies in vision, hearing, or balance, and can augment the immersive experience in virtual environments for entertainment, or professional training. This wide range of potential applications highlights the need for research on the basic psychophysics of mechanisms underlying human vibrotactile perception. One key consideration when designing tactile displays is determining the minimal possible spacing between tactile motors (tactors), by empirically assessing the maximal throughput of the skin, or, in other words, vibrotactile spatial acuity...
October 6, 2018: Experimental Brain Research. Experimentelle Hirnforschung. Expérimentation Cérébrale
Qingfeng Li, Juanjuan Peng, Ting Chen, Yan Yu, Adnan A Hyder
OBJECTIVE: Road traffic crashes impose a heavy burden in China's most populous city, Shanghai. Since early 2016, Shanghai police have started deploying high-resolution cameras and an object-detection algorithm in seatbelt enforcement. Around the same time, an international consortium on road safety launched a series of capacity trainings for law enforcement accompanied by infrastructure renovation and social marketing campaigns in Shanghai. Our objective is to assess the level and trend of seatbelt use in Shanghai over 2015-2017...
October 4, 2018: Accident; Analysis and Prevention
Perseverança Mungofa, Arnold Schumann, Laura Waldo
OBJECTIVE: This study was carried out with the purpose of testing the ability of deep learning machine vision to identify microscopic objects and geometries found in chemical crystal structures. RESULTS: A database of 6994 images taken with a light microscope showing microscopic crystal details of selected chemical compounds along with 180 images of an unknown chemical was created to train and test, respectively the deep learning models. The models used were GoogLeNet (22 layers deep network) and VGG-16 (16 layers deep network), based on the Caffe framework (University of California, Berkeley, CA) of the DIGITS platform (NVIDIA Corporation, Santa Clara, CA)...
October 5, 2018: BMC Research Notes
Isabelle Rosenthal, Sivalogeswaran Ratnasingam, Theodros Haile, Serena Eastman, Josh Fuller-Deets, Bevil R Conway
We hypothesized that the parts of scenes identified by human observers as "objects" show distinct color properties from backgrounds, and that the brain uses this information towards object recognition. To test this hypothesis, we examined the color statistics of naturally and artificially colored objects and backgrounds in a database of over 20,000 images annotated with object labels. Objects tended to be warmer colored (L-cone response > M-cone response) and more saturated compared to backgrounds...
October 1, 2018: Journal of Vision
Dace Apšvalka, Emily S Cross, Richard Ramsey
Learning new skills by watching others is important for social and motor development throughout the lifespan. Prior research has suggested that observational learning shares common substrates with physical practice at both cognitive and brain levels. In addition, neuroimaging studies have used multivariate analysis techniques to understand neural representations in a variety of domains including vision, audition, memory and action, but few studies have investigated neural plasticity in representational space...
October 3, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Shaohui Lin, Rongrong Ji, Chao Chen, Dacheng Tao, Jiebo Luo
Convolutional neural networks (CNNs) have achieved remarkable success in various computer vision tasks, which are extremely powerful to deal with massive training data by using tens of millions of parameters. However, CNNs often cost significant memory and computation consumption, which prohibits their usage in resource-limited environments such as mobile or embedded devices. To address the above issues, the existing approaches typically focus on either accelerating the convolutional layers or compressing the fully-connected layers separatedly, without pursuing a joint optimum...
October 1, 2018: IEEE Transactions on Pattern Analysis and Machine Intelligence
Emelie Gyllencreutz, Anna Chouliara, Afsaneh Alibakhshi, Mathias Tjörnvik, Eva Aring, Marita Andersson GröZ
PURPOSE: To evaluate the current vision screening criteria regarding amblyopia and refractive errors, with emphasis on screening limits and retesting, in Region Västra Götaland (VGR), Sweden. Visual acuity (VA) screening is performed by nurses at primary healthcare centres (PHCs) in 4-year-old children and at school in 6- or 7-year-old children. Children with VA <0.65 (>0.19 logMAR) at either eye are referred. If VA is 0.65 in one or both eyes, a retest is performed by nurses at PHCs and schools, the children are then referred if VA is <0...
October 2, 2018: Acta Ophthalmologica
Erkan Deniz, Abdulkadir Şengür, Zehra Kadiroğlu, Yanhui Guo, Varun Bajaj, Ümit Budak
Breast cancer is one of the leading cancer type among women in worldwide. Many breast cancer patients die every year due to the late diagnosis and treatment. Thus, in recent years, early breast cancer detection systems based on patient's imagery are in demand. Deep learning attracts many researchers recently and many computer vision applications have come out in various environments. Convolutional neural network (CNN) which is known as deep learning architecture, has achieved impressive results in many applications...
December 2018: Health Information Science and Systems
Augusta Silveira, Eurico Monteiro, Teresa Sequeira
Head and neck cancer includes a wide range of tumors that occur in several areas of the upper aerodigestive tract. Most head and neck cancer patients report treatment-related late effects (both physical and psycho-social). High-quality and patient-centered care in head and neck cancer depend on the understanding of the continuum patient's experience-the disease pathway. Healthcare has been improved by involving patients more actively in the disease process, and a few reports support that patient-reported outcomes-built around the patient's experience-given in a timely manner to oncologists are extremely valuable in oncology clinical care...
October 1, 2018: Current Treatment Options in Oncology
Zhixi Li, Stuart Keel, Chi Liu, Yifan He, Wei Meng, Jane Scheetz, Pei Ying Lee, Jonathan Shaw, Daniel Ting, Tien Wong, Hugh Taylor, Robert Chang, Mingguang He
OBJECTIVE: The goal of this study was to describe the development and validation of an artificial intelligence-based, deep learning algorithm (DLA) for the detection of referable diabetic retinopathy (DR). RESEARCH DESIGN AND METHODS: A DLA using a convolutional neural network was developed for automated detection of vision-threatening referable DR (preproliferative DR or worse, diabetic macular edema, or both). The DLA was tested by using a set of 106,244 nonstereoscopic retinal images...
October 1, 2018: Diabetes Care
Cristina Segura, Diego Halabi, Nancy Navarro
The aim of this study was to design and validate the Dental Psychomotor Skills (DePS) test as an instrument to assess dental students' psychomotor skills and to help educators adapt their academic practices to students' needs. The DePS test was created considering three of the main skills needed for dental study and practice. The dimensions measured in the test were Indirect Vision (IV) with 24 items, Instructions Follow-Up (FI) with 17 items, and Accuracy (A) with six items; each item was assessed at two stations...
October 2018: Journal of Dental Education
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