Results 101 to 110 of about 83,974 (281)
Few-Shot Classification Of Brain Cancer Images Using Meta-Learning Algorithms
EAI Endorsed Transactions on Industrial Networks and Intelligent SystemsThe primary objective of deep learning is to have good performance on a large dataset. However, when the model lacks sufficient data, it becomes a challenge to achieve high accuracy in predicting these unfamiliar classes. In fact, the real-world dataset
Tuyet-Nhi Thi Nguyen +4 more
doaj +1 more source
Improving Federated Learning Personalization via Model Agnostic Meta Learning
, 2019 Federated Learning (FL) refers to learning a high quality global model based on decentralized data storage, without ever copying the raw data. A natural scenario arises with data created on mobile phones by the activity of their users. Given the typical data heterogeneity in such situations, it is natural to ask how can the global model be personalized
Jiang, Yihan +3 more
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Journal of Clinical Psychology, EarlyView.ABSTRACT Exposure and response prevention (ERP) remains the gold‐standard psychotherapy for obsessive–compulsive disorder (OCD), yet real‐world care is limited by dropout, partial response, relapse, and phenotypes that strain habituation‐centric protocols.
Jakob Fink‐Lamotte
wiley +1 more source
JCPP Advances, EarlyView.Our umbrella synthesis found strong, often equivalent, associations between child maltreatment and all examined mental health difficulties. Different types of maltreatment appear to have comparably negative effects on mental health. If replicated, these findings may cause us to reconsider conventional wisdom that suggests some forms of CM are less ...
Barry Coughlan +7 more
wiley +1 more source
Journal of Dental Education, EarlyView.ABSTRACT Objectives Perceived professional suitability—students' judgment of whether they are well‐suited to their profession—may shift within a semester, yet longitudinal evidence in dental hygiene education is limited. We examined 6‐month changes in perceived suitability and their psychological associations.
Maya Izumi +2 more
wiley +1 more source
Jixie chuandong, 2022 Aiming at the problem that the vibration signal of planetary gearboxes has strong non-stationary characteristics， few fault samples and the dependence of traditional deep learning on data， an intelligent diagnosis method for planetary gearboxes based on ...
Xinxin Lu, Jun Ma, Yingcong Zhang
doaj
The effects of negative adaptation in Model-Agnostic Meta-Learning
, 2018 The capacity of meta-learning algorithms to quickly adapt to a variety of tasks, including ones they did not experience during meta-training, has been a key factor in the recent success of these methods on few-shot learning problems. This particular advantage of using meta-learning over standard supervised or reinforcement learning is only well founded
Deleu, Tristan, Bengio, Yoshua
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The Journal of Humanistic Counseling, EarlyView.ABSTRACT This article explores obsessive–compulsive disorder (OCD) through the framework of Gestalt therapy, specifically the “dance of reciprocity” model. It integrates phenomenological, aesthetic, and field‐oriented perspectives. Informed by research on attachment styles and emotional processes in OCD, it provides a developmentally and relationally ...
Margherita Spagnuolo Lobb +2 more
wiley +1 more source
Negative Capability and Entrepreneurial Action
Strategic Change, EarlyView.ABSTRACT Entrepreneurs operate in environments marked by uncertainty. Existing theories of entrepreneurial action largely emphasize an entrepreneur's ability to make judgments and take decisive action despite ongoing uncertainty—competencies primarily supported by what we term positive capability (PC).
Jasper Brinkerink
wiley +1 more source
CSAC-Net: Fast Adaptive sEMG Recognition through Attention Convolution Network and Model-Agnostic Meta-Learning. [PDF]
Sensors (Basel), 2022 Fan X, Zou L, Liu Z, He Y, Zou L, Chi R.
europepmc +1 more source