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Video-based learning

Kristiina Janhonen, Kaisa Torkkeli, Johanna Mäkelä
This exploratory article examines the novel term food sense and informal learning in the context of home cooking. Its theory draws from Dewey's work and from his notions of reflexive thought and action. The data consist of a transcribed audio recording of an in-depth, video-based, stimulated-recall (SR) interview. The auto-ethnographic videos were used to stimulate conversation during the interview and were previously collected as part of a broader research project on home cooking in a Finnish family context...
August 14, 2018: Appetite
Shanley B Deal, Adnan A Alseidi, Jeffrey G Chipman, Jeffrey Gauvin, Michael Meara, Richard Sidwell, Dimitrios Stefanidis, Paul J Schenarts
OBJECTIVE: Faculty teaching skills are critical for effective surgical education, however, which skills are most important to be taught in a faculty development program have not been well defined. The objective of this study was to identify priorities for faculty development as perceived by surgical educators. DESIGN: We used a modified Delphi methodology to assess faculty perceptions of the value of faculty development activities, best learning modalities, as well as barriers and priorities for faculty development...
August 13, 2018: Journal of Surgical Education
Elise Epaillard, Nizar Bouguila
Learning a hidden Markov model (HMM) is typically based on the computation of a likelihood which is intractable due to a summation over all possible combinations of states and mixture components. This estimation is often tackled by a maximization strategy, which is known as the Baum-Welch algorithm. However, some drawbacks of this approach have led to the consideration of Bayesian methods that add a prior over the parameters in order to work with the posterior probability and the marginal likelihood. These approaches can lead to good models but to the cost of extremely long computations (e...
August 8, 2018: IEEE Transactions on Neural Networks and Learning Systems
Maria Magdalena Buijs, Mohammed Hossain Ramezani, Jürgen Herp, Rasmus Kroijer, Morten Kobaek-Larsen, Gunnar Baatrup, Esmaeil S Nadimi
Background and study aims:  The aim of this study was to develop a machine learning-based model to classify bowel cleansing quality and to test this model in comparison to a pixel analysis model and assessments by four colon capsule endoscopy (CCE) readers. Methods:  A pixel analysis and a machine learning-based model with four cleanliness classes (unacceptable, poor, fair and good) were developed to classify CCE videos. Cleansing assessments by four CCE readers in 41 videos from a previous study were compared to the results both models yielded in this pilot study...
August 2018: Endoscopy International Open
Marcus R Watson, Benjamin Voloh, Milad Naghizadeh, Thilo Womelsdorf
Many studies of vision and cognition require novel three-dimensional object sets defined by a parametric feature space. Creating such sets and verifying that they are suitable for a given task, however, can be time-consuming and effortful. Here we present a new set of multidimensional objects, Quaddles, designed for studies of feature-based learning and attention, but adaptable for many research purposes. Quaddles have features that are all equally visible from any angle around the vertical axis and can be designed to be equally discriminable along feature dimensions; these objects do not show strong or consistent response biases, with a small number of quantified exceptions...
August 7, 2018: Behavior Research Methods
Xuezhi Xiang, Mingliang Zhai, Ning Lv, Abdulmotaleb El Saddik
Vehicle counting from an unmanned aerial vehicle (UAV) is becoming a popular research topic in traffic monitoring. Camera mounted on UAV can be regarded as a visual sensor for collecting aerial videos. Compared with traditional sensors, the UAV can be flexibly deployed to the areas that need to be monitored and can provide a larger perspective. In this paper, a novel framework for vehicle counting based on aerial videos is proposed. In our framework, the moving-object detector can handle the following two situations: static background and moving background...
August 4, 2018: Sensors
A Buia, S Farkas
BACKGROUND: The 3D laparoscopy is currently under intensive discussion. At the moment the majority of newly acquired laparoscopy systems include the 3D technique. New 4K systems, which will be offered in combination with 3D, are complicating the decision-making when buying new laparoscopic systems. The aim of the article is to show the advantages and possible limitations of 3D laparoscopy. Furthermore, the position of 3D laparoscopy in the current video market is evaluated. MATERIAL AND METHODS: This study was based on an up to date literature search in PubMed...
August 3, 2018: Der Chirurg; Zeitschrift Für Alle Gebiete der Operativen Medizen
Elizabeth Renner, Jessica P White, Antonia F de C Hamilton, Francys Subiaul
Humans often learn new things via imitation. Here we draw on studies of imitation in children to characterise the brain system(s) involved in the imitation of different sequence types using functional magnetic resonance imaging. On each trial, healthy adult participants learned one of two rule types governing the sequencing of three pictures: a motor-spatial rule (in the spatial task) or an object-based rule (in the cognitive task). Sequences were learned via one of three demonstration types: a video of a hand selecting items in the sequence using a joystick (Hand condition), a computer display highlighting each item in order (Ghost condition), or a text-based demonstration of the sequence (Text condition)...
2018: PloS One
Xiaoke Zhu, Xiao-Yuan Jing, Xinge You, Xinyu Zhang, Taiping Zhang
Video-based person re-identification (re-id) is an important application in practice. Since large variations exist between different pedestrian videos, as well as within each video, it's challenging to conduct re-identification between pedestrian videos. In this paper, we propose a simultaneous intra-video and inter-video distance learning (SI2DL) approach for video-based person re-id. Specifically, SI2DL simultaneously learns an intravideo distance metric and an inter-video distance metric from the training videos...
August 1, 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Cristina Simon-Martinez, Lisa Mailleux, Els Ortibus, Anna Fehrenbach, Giuseppina Sgandurra, Giovanni Cioni, Kaat Desloovere, Nicole Wenderoth, Philippe Demaerel, Stefan Sunaert, Guy Molenaers, Hilde Feys, Katrijn Klingels
BACKGROUND: Upper limb (UL) deficits in children with unilateral cerebral palsy (uCP) have traditionally been targeted with motor execution treatment models, such as modified Constraint-Induced Movement Therapy (mCIMT). However, new approaches based on a neurophysiological model such as Action-Observation Training (AOT) may provide new opportunities for enhanced motor learning. The aim of this study is to describe a randomised controlled trial (RCT) protocol investigating the effects of an intensive treatment model, combining mCIMT and AOT compared to mCIMT alone on UL function in children with uCP...
July 31, 2018: BMC Pediatrics
Claudio Ferrari, Giuseppe Lisanti, Stefano Berretti, Alberto Del Bimbo
Face recognition "in the wild" has been revolutionized by the deployment of deep learning based approaches. In fact, it has been extensively demonstrated that Deep Convolutional Neural Networks (DCNNs) are powerful enough to overcome most of the limits that affected face recognition algorithms based on hand-crafted features. These include variations in illumination, pose, expression and occlusion, to mention some. The DCNNs discriminative power comes from the fact that low- and high-level representations are learned directly from the raw image data...
July 30, 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Jian Chen, Nathan Cheng, Giovanni Cacciamani, Paul Oh, Michael Lin-Brande, Daphne Remulla, Inderbir S Gill, Andrew J Hung
PURPOSE: Robotic surgeries, especially in urology, have grown exponentially over the past decade. Various skill assessment tools have been developed. We review the present status, current challenges, and future needs of robotic evaluations, with a focus on urologic applications. MATERIALS AND METHODS: Following the Preferred Reporting Items for Systemic Review and Meta-Analysis (PRISMA), two paired investigators screened PubMed® , Scopus® and Web of Science® databases for all full text, English language articles published between 2006 and 2018 using the query (evaluation OR assessment) AND (robot-assisted surgery OR robotic surgery) AND (surgical performance OR surgical skill) AND training...
July 24, 2018: Journal of Urology
Sook Jung Kang, Hae Young Min
BACKGROUND: Although nursing students enjoy and learn from simulation practice, some experience negative feelings that may hamper their learning outcomes. PURPOSE: The purpose of this study was to understand nursing students' perceptions of psychological safety in simulation practice to provide a foundation for a safe and effective simulation learning environment. METHODS: A convenient sample of 15 undergraduate nursing students was included in this study...
July 26, 2018: Nurse Educator
Catherine Patocka, Michelle Lin, Jeremy Voros, Teresa Chan
Background: Technologic advances, free open-access medical education (FOAM or #FOAMed), and social media have increased access to clinician-oriented medical education resources and interactions at the point of care (POC); yet, how, when, and why medical providers use these resources remains unclear. To facilitate the development and design of intuitive POC resources, it is imperative that we expand our understanding of physician knowledge-seeking behavior at the POC. Methods: Individual semistructured interviews were conducted and analyzed using a qualitative, grounded theory approach...
July 2018: AEM education and training
Mai Xu, Yuhang Song, Jianyi Wang, MingLang Qiao, Liangyu Huo, Zulin Wang
Panoramic video provides immersive and interactive experience by enabling humans to control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in modeling human attention on panoramic video. This paper establishes a database collecting subjects' HM in panoramic video sequences. From this database, we find that the HM data are highly consistent across subjects. Furthermore, we find that deep reinforcement learning (DRL) can be applied to predict HM positions, via maximizing the reward of imitating human HM scanpaths through the agent's actions...
July 24, 2018: IEEE Transactions on Pattern Analysis and Machine Intelligence
Ren-Jie Huang, Chun-Yu Tsao, Yi-Pin Kuo, Yi-Chung Lai, Chi Chung Liu, Zhe-Wei Tu, Jung-Hua Wang, Chung-Cheng Chang
Recently, an upsurge of deep learning has provided a new direction for the field of computer vision and visual tracking. However, expensive offline training time and the large number of images required by deep learning have greatly hindered progress. This paper aims to further improve the computational performance of CNT which is reported to deliver 5 fps performance in visual tracking, we propose a method called Fast-CNT which differs from CNT in three aspects: firstly, an adaptive k value (rather than a constant 100) is determined for an input video; secondly, background filters used in CNT are omitted in this work to save computation time without affecting performance; thirdly, SURF feature points are used in conjunction with the particle filter to address the drift problem in CNT...
July 24, 2018: Sensors
Linwei Zhu, Yun Zhang, Shiqi Wang, Hui Yuan, Sam Kwong, Horace H S Ip
The quality of synthesized view plays an important role in the three dimensional (3D) video system. In this paper, to further improve the coding efficiency, a convolutional neural network (CNN) based synthesized view quality enhancement method for 3D High Efficiency Video Coding (HEVC) is proposed. Firstly, the distortion elimination in synthesized view is formulated as an image restoration task with the aim to reconstruct the latent distortion free synthesized image. Secondly, the learned CNN models are incorporated into 3D HEVC codec to improve the view synthesis performance for both view synthesis optimization (VSO) and the final synthesized view, where the geometric and compression distortions are considered according to the specific characteristics of synthesized view...
July 20, 2018: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Melanie L Styers, Peter A Van Zandt, Katherine L Hayden
Although development of critical thinking skills has emerged as an important issue in undergraduate education, implementation of pedagogies targeting these skills across different science, technology, engineering, and mathematics disciplines has proved challenging. Our goal was to assess the impact of targeted interventions in 1) an introductory cell and molecular biology course, 2) an intermediate-level evolutionary ecology course, and 3) an upper-level biochemistry course. Each instructor used Web-based videos to flip some aspect of the course in order to implement active-learning exercises during class meetings...
September 2018: CBE Life Sciences Education
Hasan Naveed, Richard Hudson, Manaf Khatib, Fernando Bello
Background: Learning the skills required for open surgery is essential for trainee progression towards more advanced technical procedures. Simulation supports skill enhancement at a time when exposure to actual surgical procedures and traditional apprentice-based teaching has declined. The proliferation of smartphone and tablet devices with rich, touch sensitive displays and increasing processing power makes a compelling argument for expanding accessibility further by development of mobile virtual simulations for training on demand in any setting, at any time...
2018: Advances in Simulation
Richard Cookson, Shehzad Ali, Aki Tsuchiya, Miqdad Asaria
In principle, questionnaire data on public views about hypothetical trade-offs between improving total health and reducing health inequality can provide useful normative health inequality aversion parameter benchmarks for policymakers faced with real trade-offs of this kind. However, trade-off questions can be hard to understand, and one standard type of question finds that a high proportion of respondents-sometimes a majority-appear to give exclusive priority to reducing health inequality. We developed and tested two e-learning interventions designed to help respondents understand this question more completely...
July 22, 2018: Health Economics
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