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IEEE transactions on cybernetics
Aug 18, 2022
The superiority of deeply learned representations relies on large-scale labeled datasets. However, annotating data are usually expensive or even infeasible in some scenarios. To address this problem, we propose an unsupervised method to leverage inst...
Neural networks : the official journal of the International Neural Network Society
Aug 17, 2022
Structural deep clustering involves the use of neural networks for fusing semantic and structural representations for clustering tasks, and it has been receiving increasing attention. In some pioneering works, auto-encoder (AE)-specific representatio...
Scientific reports
Aug 16, 2022
With advances in deep learning and natural language processing (NLP), the analysis of medical texts is becoming increasingly important. Nonetheless, despite the importance of processing medical texts, no research on Korean medical-specific language m...
Computational intelligence and neuroscience
Aug 12, 2022
Vulnerability detection technology has become a hotspot in the field of software security, and most of the current methods do not have a complete consideration during code characterizing, which leads to problems such as information loss. Therefore, t...
Frontiers in public health
Aug 10, 2022
Handwritten prescriptions and radiological reports: doctors use handwritten prescriptions and radiological reports to give drugs to patients who have illnesses, injuries, or other problems. Clinical text data, like physician prescription visuals and ...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
It is important and challenging to infer stochastic latent semantics for natural language applications. The difficulty in stochastic sequential learning is caused by the posterior collapse in variational inference. The input sequence is disregarded i...
Proceedings of the National Academy of Sciences of the United States of America
Aug 3, 2022
Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However,...
IEEE transactions on neural networks and learning systems
Aug 3, 2022
In this article, we focus on decomposing latent representations in generative adversarial networks or learned feature representations in deep autoencoders into semantically controllable factors in a semisupervised manner, without modifying the origin...
Computational intelligence and neuroscience
Jul 31, 2022
Latent Dirichlet Allocation (LDA) is an approach to unsupervised learning that aims to investigate the semantics among words in a document as well as the influence of a subject on a word. As an LDA-based model, Joint Sentiment-Topic (JST) examines th...
Computational intelligence and neuroscience
Jul 30, 2022
With the rise of unmanned driving and intelligent transportation research, great progress has been made in vehicle detection technology. The purpose of this paper is employing the method of deep learning to study the vehicle detection algorithm, in w...