AIMC Topic: Transfer, Psychology

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A novel deep transfer learning method based on explainable feature extraction and domain reconstruction.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Although deep transfer learning has made significant progress, its "black-box" nature and unstable feature adaptation remain key obstacles. This study proposes a multi-stage deep transfer learning method, called XDTL, which combines explainable featu...
Humans Neural Networks, Computer Algorithms Deep Learning Transfer, Psychology
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Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

Tomography (Ann Arbor, Mich.) Mar 1, 2019
We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre-...
Humans Tomography, X-Ray Computed Sensitivity and Specificity Antineoplastic Agents Deep Learning ROC Curve Decision Support Systems, Clinical Treatment Outcome Neoadjuvant Therapy Urinary Bladder Neoplasms Drug Monitoring Radiographic Image Interpretation, Computer-Assisted Cystectomy Urography Transfer, Psychology
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Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Current sleep medicine relies on the supervised analysis of polysomnographic measurements, comprising amongst others electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG) signals. Convolutional neural networks (CNN) provide an ...
Humans Neural Networks, Computer Databases, Factual Deep Learning Electroencephalography Electromyography Sleep Sleep Wake Disorders Electrooculography Sleep Stages Transfer, Psychology
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Multisource Transfer Double DQN Based on Actor Learning.

IEEE transactions on neural networks and learning systems Jun 1, 2018
Deep reinforcement learning (RL) comprehensively uses the psychological mechanisms of "trial and error" and "reward and punishment" in RL as well as powerful feature expression and nonlinear mapping in deep learning. Currently, it plays an essential ...
Humans Neural Networks, Computer Machine Learning Algorithms Computer Simulation Reinforcement, Psychology Transfer, Psychology
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