Results 91 to 100 of about 252,636 (309)
Style Augmentation: Data Augmentation via Style Randomization
CoRR, 2018 We introduce style augmentation, a new form of data augmentation based on random style transfer, for improving the robustness of convolutional neural networks (CNN) over both classification and regression based tasks. During training, our style augmentation randomizes texture, contrast and color, while preserving shape and semantic content.
Philip T. G. Jackson +4 more
openaire +4 more sources
Intelligent Tutoring Systems for Adult Learning in STEM Disciplines
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Intelligent tutoring systems (ITS) are reshaping adult learning in STEM by providing adaptive, data‐driven instruction across classrooms, workplaces, and informal environments. In the context of ITS, this article compares generative AI, which creates personalized explanations and practice materials, with explainable AI, which focuses on ...
Jill Zarestky, Amanda R. Lager Gleason
wiley +1 more source
, 2020 This work presents efforts to augment the performance of data-driven machine learning algorithms for reaction template recommendation used in computer-aided synthesis planning software.
Brian, Barnes +3 more
core +1 more source
Survey of Image Data Augmentation Techniques Based on Deep Learning [PDF]
Jisuanji kexueIn recent years,deep learning has demonstrated excellent performance in many computer vision tasks such as image classification,object detection,and image segmentation.Deep neural networks usually rely on a large amount of training data to avoid ...
SUN Shukui, FAN Jing, SUN Zhongqing, QU Jinshuai, DAI Tingting
doaj +1 more source
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT Mental well‐being is central to adult learner success, yet many adult education institutions lack capacity to provide timely and accessible support. This article examines how artificial intelligence (AI) can strengthen mental health–adjacent supports in adult and continuing higher education, with attention to professional practice and ...
Adam L. McClain, Thomas Wade
wiley +1 more source
Reinforcement Learning with Augmented Data
CoRR, 2020 Learning from visual observations is a fundamental yet challenging problem in Reinforcement Learning (RL). Although algorithmic advances combined with convolutional neural networks have proved to be a recipe for success, current methods are still lacking on two fronts: (a) data-efficiency of learning and (b) generalization to new environments.
Michael Laskin +5 more
openaire +3 more sources
New Directions for Adult and Continuing Education, EarlyView.ABSTRACT This article examines the evolving role of organizational leadership amidst the rapid advancements in artificial intelligence (AI). It explores a broadly experienced and documented crisis in leadership, due in part to the disruptive nature of AI and emerging technology.
Rachel Wlodarsky, Davin Carr Chellman
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Introduction Progressive Supranuclear Palsy (PSP) is a neurodegenerative ‘tauopathy’ with predominating pathology in the basal ganglia and midbrain. Caudal tau spread frequently implicates the cerebellum; however, the pattern of atrophy remains equivocal.
Chloe Spiegel +8 more
wiley +1 more source
Data Augmentation for Meta-Learning
CoRR, 2020 15 pages, 3 figures, Accepted to ICML ...
Renkun Ni +4 more
openaire +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu +10 more
wiley +1 more source