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Vision training

Ahsiah Ismail, Mohd Yamani Idna Idris, Mohamad Nizam Ayub, Lip Yee Por
Smart manufacturing enables an efficient manufacturing process by optimizing production and product transaction. The optimization is performed through data analytics that requires reliable and informative data as input. Therefore, in this paper, an accurate data capture approach based on a vision sensor is proposed. Three image recognition methods are studied to determine the best vision-based classification technique, namely Bag of Words (BOW), Spatial Pyramid Matching (SPM) and Convolutional Neural Network (CNN)...
December 10, 2018: Sensors
Dor Oppenheim, Guy Shani, Orly Erlich, Leah Tsror
Many plant diseases have distinct visual symptoms which can be used to identify and classify them correctly. This paper presents a potato disease classification algorithm which leverages these distinct appearances and the recent advances in computer vision made possible by deep learning. The algorithm uses a deep convolutional neural network training it to classify the tubers into five classes, namely, four disease classes and a healthy potato class. The database of images used in this study, containing potato tubers of different cultivars, sizes and diseases, was acquired, classified, and labeled manually by experts...
December 13, 2018: Phytopathology
Hermina Harnagea
Accelerated ageing of the population results in an ever-increasing number of functionally dependent elderly persons. Even healthy older people experience self-care deficits due to decreased mobility, endurance and sensory loss. Residents in long-term care centres depend on caregivers for the majority of their activities of daily living.Dental services for functionally dependent seniors generally remain inadequate. Several factors may explain this situation, including the absence of government guidelines and the lack of initial and continuing training of both dental and non-dental personnel...
May 2018: Santé Publique: Revue Multidisciplinaire Pour la Recherche et L'action
Nicholas Baker, Hongjing Lu, Gennady Erlikhman, Philip J Kellman
Deep convolutional networks (DCNNs) are achieving previously unseen performance in object classification, raising questions about whether DCNNs operate similarly to human vision. In biological vision, shape is arguably the most important cue for recognition. We tested the role of shape information in DCNNs trained to recognize objects. In Experiment 1, we presented a trained DCNN with object silhouettes that preserved overall shape but were filled with surface texture taken from other objects. Shape cues appeared to play some role in the classification of artifacts, but little or none for animals...
December 7, 2018: PLoS Computational Biology
Fausto Milletari, Johann Frei, Moustafa Aboulatta, Gerome Vivar, Seyed-Ahmad Ahmadi
BACKGROUND: Deep learning has been recently applied to a multitude of computer vision and medical image analysis problems. Although recent research efforts have improved the state of the art, most of the methods cannot be easily accessed, compared or used by other researchers or clinicians. Even if developers publish their code and pre-trained models on the internet, integration in stand-alone applications and existing workflows is often not straightforward, especially for clinical research partners...
December 5, 2018: IEEE Journal of Biomedical and Health Informatics
Sharmeela Saha, Jay B Wish
The responsibilities of a dialysis unit medical director are specified in the ESRD Conditions for Coverage and encompass multiple quality, safety, and educational domains. Many of these responsibilities require leadership skills that are neither intuitive nor acquired as part of the medical director's training. An effective medical director is able to shape the culture of the dialysis facility such that patients and staff feel free to communicate their concerns regarding suboptimal processes without fear of retribution, and there is a continuous iterative process of quality improvement and safety, which values input from all stakeholders...
November 2018: Advances in Chronic Kidney Disease
Brooke J Vetter, Loranzie S Rogers, Allen F Mensinger
Non-physical barriers, including the use of underwater strobe lights alone or paired with sound or bubbles, are being considered as a means to prevent the upstream migration of invasive silver carp Hypophthalmichthys molitrix and bighead carp H. nobilis. To optimize potential optical deterrents, it is necessary to understand the visual sensitivity of the fishes. Dark-adapted H. molitrix and H. nobilis were found to possess broad visual sensitivity between 470 nm to 620 nm with peak spectral sensitivity at 540 nm for H...
December 7, 2018: Journal of Fish Biology
Edlamar Kátia Adamy, Denise Antunes de Azambuja Zocche, Carine Vendruscolo, José Luis Guedes Dos Santos, Miriam de Abreu Almeida
OBJECTIVE: To present the validation of a theoretical model through conversation circles in a qualitative research guided by the Grounded Theory. METHOD: Study carried out from a thesis developed in a reference hospital in the south region of Brazil. Two conversation circles happened, with participation of representatives of the "Training Prism", in the months of October and November, 2016. RESULTS: The conversation circle enabled an in depth dialogic approach of the subject of research, broadening the vision on the phenomenon and on the research...
November 2018: Revista Brasileira de Enfermagem
Behnoosh Momin, Ena Wanliss, Lumbe Davis, Julie S Townsend, Kerri Lopez, Brooke Steele
Achieving health equity requires addressing social determinants of health. Promoting health equity as it relates to cancer control is one of six priorities of the National Comprehensive Cancer Control Program (NCCCP). This article describes recent activities implemented by three NCCCP awardees (North-west Portland Area Indian Health Board, Kansas, Michigan) and the CDC-funded National Behavior Health Network (NBHN), whose aim is to reduce health disparities among those with mental health and/or substance disorders...
December 4, 2018: Cancer Causes & Control: CCC
Yicheng Chen, Javier E Villanueva-Meyer, Melanie A Morrison, Janine M Lupo
Cerebral microbleeds, which are small focal hemorrhages in the brain that are prevalent in many diseases, are gaining increasing attention due to their potential as surrogate markers of disease burden, clinical outcomes, and delayed effects of therapy. Manual detection is laborious and automatic detection and labeling of these lesions is challenging using traditional algorithms. Inspired by recent successes of deep convolutional neural networks in computer vision, we developed a 3D deep residual network that can distinguish true microbleeds from false positive mimics of a previously developed technique based on traditional algorithms...
December 3, 2018: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
Mirella T S Barboni, Zsuzsanna Récsán, Zsuzsanna Szepessy, Mónika Ecsedy, Balázs Vince Nagy, Dora F Ventura, Zoltán Zsolt Nagy, János Németh
Biofeedback training has been used to improve fixation stability in subjects with central vision loss, but the psychophysiological mechanisms underlying the functional improvements resulted was not reported. The aim of this study was to investigate the effects of microperimetric biofeedback training on different visual functions and self-reported quality of vision in subjects with age-related macular degeneration. This case-control study included six subjects (72.0 ± 6.1 years of age) diagnosed with age-related macular degeneration (wet or dry) with low vision (best corrected visual acuity ranging from 0...
November 30, 2018: Applied Psychophysiology and Biofeedback
Ruba Alkadi, Fatma Taher, Ayman El-Baz, Naoufel Werghi
We address the problem of prostate lesion detection, localization, and segmentation in T2W magnetic resonance (MR) images. We train a deep convolutional encoder-decoder architecture to simultaneously segment the prostate, its anatomical structure, and the malignant lesions. To incorporate the 3D contextual spatial information provided by the MRI series, we propose a novel 3D sliding window approach, which preserves the 2D domain complexity while exploiting 3D information. Experiments on data from 19 patients provided for the public by the Initiative for Collaborative Computer Vision Benchmarking (I2CVB) show that our approach outperforms traditional pattern recognition and machine learning approaches by a significant margin...
November 30, 2018: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
Seunghwan Seo, Seo-Hyeon Jo, Sungho Kim, Jaewoo Shim, Seyong Oh, Jeong-Hoon Kim, Keun Heo, Jae-Woong Choi, Changhwan Choi, Saeroonter Oh, Duygu Kuzum, H-S Philip Wong, Jin-Hong Park
The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensing functions together on h-BN/WSe2 heterostructure. This device mimics the colored and color-mixed pattern recognition capabilities of the human vision system when arranged in an optic-neural network. Our synaptic device demonstrates a close to linear weight update trajectory while providing a large number of stable conduction states with less than 1% variation per state...
November 30, 2018: Nature Communications
Daniel Jimenez-Carretero, Vahid Abrishami, Laura Fernández-de-Manuel, Irene Palacios, Antonio Quílez-Álvarez, Alberto Díez-Sánchez, Miguel A Del Pozo, María C Montoya
Toxicity is an important factor in failed drug development, and its efficient identification and prediction is a major challenge in drug discovery. We have explored the potential of microscopy images of fluorescently labeled nuclei for the prediction of toxicity based on nucleus pattern recognition. Deep learning algorithms obtain abstract representations of images through an automated process, allowing them to efficiently classify complex patterns, and have become the state-of-the art in machine learning for computer vision...
November 30, 2018: PLoS Computational Biology
Jahanara Miah, Piers Dawes, Iracema Leroi, Suzanne Parsons, Bella Starling
Plain English summary: Involving older people with dementia in research is increasingly recognised as important to ensure that research is relevant and beneficial for older people with dementia. But researchers need to know how best to involve older people with dementia and to be able to show the benefits of involving older people with dementia in dementia research.This paper describes a research plan to explore the involvement of older people with dementia and age-related hearing and/or vision impairment in a European research project investigating the combined impact of dementia with hearing and/or vision impairment...
2018: Research Involvement and Engagement
Yang Liu, Noelle Rb Stiles, Markus Meister
To restore vision for the blind, several prosthetic approaches have been explored that convey raw images to the brain. So far, these schemes all suffer from a lack of bandwidth. An alternate approach would restore vision at the cognitive level, bypassing the need to convey sensory data. A wearable computer captures video and other data, extracts important scene knowledge, and conveys that to the user in compact form. Here, we implement an intuitive user interface for such a device using augmented reality: each object in the environment has a voice and communicates with the user on command...
November 27, 2018: ELife
Xin Zhao, Lin Cong
BACKGROUND: Orthopedic operating room (OR) nurses entail specialized skills and training, which are not part of the regular curricula at most nursing college. Instead, many nursing students' exposure to orthopedic care in the orthopedic range is limited to occasional observational assignments. Additionally, teamwork is an important factor affecting the performance of the orthopedic OR nurses. This results in a knowledge gap in clinical nursing education. Problem and scripting based learning (PSBL) method is a crucial tool of pre-operative prepared improvement...
November 16, 2018: Nurse Education Today
Sandra M Fox, Paul Koons, Sally H Dang
Visual dysfunctions and symptoms are commonly experienced after even mild traumatic brain injury (TBI) despite excellent visual acuity. All individuals who have experienced a TBI/concussion should be screened for vision symptoms and visual dysfunction. A TBI-specific eye examination is necessary to identify the visual sequelae of TBI and address any vision/ocular issues that may be contributing to other post-TBI complaints. A vision rehabilitation plan that includes vision therapy can improve visual dysfunction secondary to TBI...
February 2019: Physical Medicine and Rehabilitation Clinics of North America
Caleb Busch, Ryu Nakadate, Munenori Uemura, Satoshi Obata, Takahiro Jimbo, Makoto Hashizume
INTRODUCTION: The purpose of this study was to assess robot-assisted suturing skills on a laparoscopic intestinal anastomosis model by using a novel computerized objective assessment system. METHODS: This study compared the suturing skills of 13 surgically naïve participants on an artificial intestinal anastomosis model that mimics real tissue. Each examinee sutured using da Vinci robot assistance under 2-D and 3-D visualization and with conventional laparoscopy (CL)...
November 21, 2018: Asian Journal of Endoscopic Surgery
Amir Baghdadi, Ahmed A Hussein, Youssef Ahmed, Lora A Cavuoto, Khurshid A Guru
PURPOSE: To develop and validate an automated assessment of surgical performance (AASP) system for objective and computerized assessment of pelvic lymph node dissection (PLND) as an integral part of robot-assisted radical cystectomy (RARC) using console-feed videos recorded during live surgery. METHODS: Video recordings of 20 PLNDs were included. The quality of lymph node clearance was assessed based on the features derived from the computer vision process which include: the number and cleared area of the vessels/nerve (N-Vs); image median color map; and mean entropy (measures the level of disorganization) in the video frame...
November 20, 2018: International Journal of Computer Assisted Radiology and Surgery
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