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Video-based learning

Xin Huang, Yuxin Peng, Mingkuan Yuan
Cross-modal retrieval has drawn wide interest for retrieval across different modalities (such as text, image, video, audio, and 3-D model). However, existing methods based on a deep neural network often face the challenge of insufficient cross-modal training data, which limits the training effectiveness and easily leads to overfitting. Transfer learning is usually adopted for relieving the problem of insufficient training data, but it mainly focuses on knowledge transfer only from large-scale datasets as a single-modal source domain (such as ImageNet) to a single-modal target domain...
December 5, 2018: IEEE Transactions on Cybernetics
Yuming Fang, Guanqun Ding, Jia Li, Zhijun Fang
Stereoscopic saliency detection plays an important role in various stereoscopic video processing applications. However, conventional stereoscopic video saliency detection methods mainly use independent low-level features instead of extracting them automatically, and thus, they ignore the intrinsic relationship between the spatial and temporal information. In this paper, we propose a novel stereoscopic video saliency detection method based on 3D convolutional neural networks, namely Deep 3D Video Saliency (Deep3DSaliency)...
December 5, 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Martha Godfrey, Alexandra A Rosser, Carla M Pugh, Ajit K Sachdeva, Sarah Sullivan
BACKGROUND: Given their variegated backgrounds, surgeons taking continuing medical education (CME) courses possess different learning needs. This study examines the relationship between surgeons' levels of experience and the questions they asked in a simulation-based CME course. METHODS: We analyzed transcribed audio-video data collected from surgeons participating in a simulated laparoscopic hernia repair CME course and identified four types of questions learners posed to their instructors...
November 27, 2018: American Journal of Surgery
Wen-Sheng Chu, Fernando De la Torre, Jeffrey F Cohn
Facial action units (AUs) may be represented spatially, temporally , and in terms of their correlation . Previous research focuses on one or another of these aspects or addresses them disjointly. We propose a hybrid network architecture that jointly models spatial and temporal representations and their correlation. In particular, we use a Convolutional Neural Network (CNN) to learn spatial representations, and a Long Short-Term Memory (LSTM) to model temporal dependencies among them. The outputs of CNNs and LSTMs are aggregated into a fusion network to produce per-frame prediction of multiple AUs...
January 2019: Image and Vision Computing
Gary Sutkin, Eliza B Littleton, Steven L Kanter
BACKGROUND: Surgical residents desire independent operating experience but recognize that attendings have a responsibility to keep cases as short as possible. METHODS: We analyzed video and interviews of attending surgeons related to more than 400 moments in which the resident was the primary operator. We examined these moments for themes related to timing and pace. RESULTS: Our surgeons encouraged the residents to speed up when patient safety could be jeopardized by the case moving too slowly...
November 27, 2018: American Journal of Surgery
Panagiota Zgoura, Daniel Hettich, Jonathan Natzel, Fedai Özcan, Boris Kantzow
BACKGROUND/AIM: Peritonitis rates in peritoneal dialysis (PD) vary considerably not only across countries but also between centers in the same country. Patient education has been shown to significantly reduce infection rates but up till now training lacks standardization with patients being trained using different methods and media (e.g., illustrations, videos). As a result, patients may be insufficiently experienced in performing PD, which might be one of the causes for high peritonitis rates...
December 6, 2018: Blood Purification
Omar Akhand, Laura J Balcer, Steven L Galetta
PURPOSE OF REVIEW: To review emerging vision-based assessments in the evaluation of concussion. RECENT FINDINGS: Involvement of the visual pathways is common following concussion, the mildest form of traumatic brain injury. The visual system contains widely distributed networks that are prone to neurophysiologic changes after a concussion, resulting in visual symptoms and ocular motor dysfunction. Vision-based testing is increasingly used to improve detection and assess head injury...
November 30, 2018: Current Opinion in Neurology
Adam M Persky
INTRODUCTION: Students enrolled in professional pharmacy programs tend to have high prior academic achievement. This achievement may be predicated on their learning strategies. However, when entering a professional program, it is unclear if their strategies change to adopt to a new, more rigorous academic environment. The purpose of this research note is to document a single cohort of students' learning strategies over time within a doctor of pharmacy (PharmD) curriculum. METHODS: A single cohort from the University of North Carolina at Chapel Hill Eshelman School of Pharmacy received yearly surveys regarding their learning strategies used during the past academic year...
November 2018: Currents in Pharmacy Teaching & Learning
Miao Wang, Guo-Ye Yang, Jin-Kun Lin, Song-Hai Zhang, Ariel Shamir, Shao-Ping Lu, Shi-Min Hu
Video stabilization techniques are essential for most hand-held captured videos due to high-frequency shakes. Several 2D, 2.5D and 3D-based stabilization techniques have been presented previously, but to our knowledge, no solutions based on deep neural networks had been proposed to date. The main reason for this omission is shortage in training data as well as the challenge of modeling the problem using neural networks. In this paper, we present a video stabilization technique using a convolutional neural network...
November 30, 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Rosanna Viglialoro, Nicola Esposito, Sara Condino, Fabrizio Cutolo, Simone Guadagni, Marco Gesi, Mauro Ferrari, Vincenzo Ferrari
Hybrid surgical simulators based on Augmented Reality (AR) solutions benefit from the advantages of both the box trainers and the Virtual Reality simulators. This paper reports on the results of a long development stage of a hybrid simulator for laparoscopic cholecystectomy that integrates real and the virtual components. We first outline the specifications of the AR simulator and then we explain the strategy adopted for implementing it based on a careful selection of its simulated anatomical components, and characterized by a real-time tracking of both a target anatomy and of the laparoscope...
November 28, 2018: IEEE Transactions on Bio-medical Engineering
Tin-Kwang Lin, Pao-Ta Yu, Lian-Yu Lin, Ping-Yen Liu, Yi-Da Li, Chiu-Tien Hsu, Yih-Ru Cheng, Chun-Yin Yeh, Shu-Shu Wong, Shih-An Pai, Huey-Ling Shee, Chia-Ying Weng
BACKGROUND: Many patients with coronary artery heart disease are unable to access traditional psychosocial rehabilitation conducted face to face due to excessive travel distance. Therefore, this study developed and assessed the feasibility and acceptability of an 8-week Internet-based cognitive-behavior group therapy program, described the patterns of use and measured change in risk factors. METHODS: This study adopted an online video conference system, JointNet, to maintain group interaction functions similar to face to face groups online, and also built an self-learning platform to deliver psychoeducation content and cognitive-behavior therapy related materials and homework...
2018: PloS One
Hyun Park, Jianbo Shi
A first-person video delivers what the camera wearer (actor) experiences through physical interactions with surroundings. In this paper, we focus on a problem of Force from Motion-estimating the active force and torque exerted by the actor to drive her/his activity-from a first-person video. We use two physical cues inherited in the first-person video. (1) Ego-motion: the camera motion is generated by a resultant of force interactions, which allows us to understand the effect of the active force using Newtonian mechanics...
November 26, 2018: IEEE Transactions on Pattern Analysis and Machine Intelligence
Jennie C De Gagne, Sang S Kim, Ellen R Schoen, Hyeyoung K Park
BACKGROUND: Web-based education is one of the leading learning pedagogies in health professions education. Students have access to a multitude of opinions, knowledge, and resources on Web, but communication among students in Web-based courses is complicated. Technology adds a filter that makes it difficult to decipher the emotions behind words or read nonverbal cues. This is a concern because students benefit more from Web-based classes when they have a high perception of social presence...
November 26, 2018: JMIR Medical Education
Jiaying Liu, Sifeng Xia, Wenhan Yang, Mading Li, Dong Liu
Fractional interpolation is used to provide sub-pixel level references for motion compensation in the inter prediction of video coding, which attempts to remove temporal redundancy in video sequences. Traditional handcrafted fractional interpolation filters face the challenge of modeling discontinuous regions in videos, while existing deep learning based methods are either designed for a single quantization parameter (QP), only generate half-pixel samples, or need to train a model for each subpixel position...
November 22, 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
David A Cook, Becca L Gas, David R Farley, Matthew Lineberry, Nimesh D Naik, Francisco J Cardenas Lara, Anthony R Artino
OBJECTIVES: An incremental (growth) theory of intelligence (mindset), compared with an entity (fixed) mindset, has been associated with improved motivation and performance. Interventions to induce incremental beliefs have improved performance on non-surgical motor tasks. We sought to evaluate the impact of 2 brief interventions to induce incremental beliefs in the context of learning a surgical task. DESIGN: Two randomized experiments. PARTICIPANTS AND SETTING: Secondary school students participating in medical simulation-based training activities at an academic medical center...
November 22, 2018: Journal of Surgical Education
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
Thanh Nguyen, Yujia Xue, Yunzhe Li, Lei Tian, George Nehmetallah
Convolutional neural networks (CNNs) have gained tremendous success in solving complex inverse problems. The aim of this work is to develop a novel CNN framework to reconstruct video sequences of dynamic live cells captured using a computational microscopy technique, Fourier ptychographic microscopy (FPM). The unique feature of the FPM is its capability to reconstruct images with both wide field-of-view (FOV) and high resolution, i.e. a large space-bandwidth-product (SBP), by taking a series of low resolution intensity images...
October 1, 2018: Optics Express
Hassan Al Hajj, Mathieu Lamard, Pierre-Henri Conze, Soumali Roychowdhury, Xiaowei Hu, Gabija Maršalkaitė, Odysseas Zisimopoulos, Muneer Ahmad Dedmari, Fenqiang Zhao, Jonas Prellberg, Manish Sahu, Adrian Galdran, Teresa Araújo, Duc My Vo, Chandan Panda, Navdeep Dahiya, Satoshi Kondo, Zhengbing Bian, Arash Vahdat, Jonas Bialopetravičius, Evangello Flouty, Chenhui Qiu, Sabrina Dill, Anirban Mukhopadhyay, Pedro Costa, Guilherme Aresta, Senthil Ramamurthy, Sang-Woong Lee, Aurélio Campilho, Stefan Zachow, Shunren Xia, Sailesh Conjeti, Danail Stoyanov, Jogundas Armaitis, Pheng-Ann Heng, William G Macready, Béatrice Cochener, Gwenolé Quellec
Surgical tool detection is attracting increasing attention from the medical image analysis community. The goal generally is not to precisely locate tools in images, but rather to indicate which tools are being used by the surgeon at each instant. The main motivation for annotating tool usage is to design efficient solutions for surgical workflow analysis, with potential applications in report generation, surgical training and even real-time decision support. Most existing tool annotation algorithms focus on laparoscopic surgeries...
November 16, 2018: Medical Image Analysis
Aniruddha K Deshpande, Shruti Balvalli Deshpande, Colleen O'Brien
Purpose: As more people experience tinnitus, social awareness of tinnitus has consequently increased, due in part to the Internet. Social media platforms are being used increasingly by patients to seek health-related information for various conditions including tinnitus. These online platforms may be used to seek guidance from and share experiences with individuals suffering from a similar disorder. Some social media platforms can also be used to communicate with health care providers...
September 19, 2018: American Journal of Audiology
Ahmad Delforouzi, Bhargav Pamarthi, Marcin Grzegorzek
Object tracking in challenging videos is a hot topic in machine vision. Recently, novel training-based detectors, especially using the powerful deep learning schemes, have been proposed to detect objects in still images. However, there is still a semantic gap between the object detectors and higher level applications like object tracking in videos. This paper presents a comparative study of outstanding learning-based object detectors such as ACF, Region-Based Convolutional Neural Network (RCNN), FastRCNN, FasterRCNN and You Only Look Once (YOLO) for object tracking...
November 16, 2018: Sensors
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