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Unsupervised feature learning based on autoencoder for epileptic seizures prediction
Epilepsy is one of the most common neurological diseases in the world. It’s essential to predict epileptic seizures since it can provide patients...
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Deep boundary-aware clustering by jointly optimizing unsupervised representation learning
Deep clustering obtains feature representation generally and then performs clustering for high dimension real-world data. However, conventional...
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Dynamic parameterized learning for unsupervised domain adaptation
Unsupervised domain adaptation enables neural networks to transfer from a labeled source domain to an unlabeled target domain by learning...
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Predicting document novelty: an unsupervised learning approach
In the age of information deluge, it is pivotal to have access to information or knowledge which is not just relevant but also, novel. Knowledge...
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Learning deep latent space for unsupervised violence detection
Numerous violent actions occur in the world every day, affecting victims mentally and physically. To reduce violence rates in society, an automatic...
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Category-Level Contrastive Learning for Unsupervised Hashing in Cross-Modal Retrieval
Unsupervised hashing for cross-modal retrieval has received much attention in the data mining area. Recent methods rely on image-text paired data to...
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Representation learning via an integrated autoencoder for unsupervised domain adaptation
The purpose of unsupervised domain adaptation is to use the knowledge of the source domain whose data distribution is different from that of the...
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AtomGAN: unsupervised deep learning for fast and accurate defect detection of 2D materials at the atomic scale
The extraction of atomic-level material features from electron microscope images is crucial for studying structure-property relationships and...
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Meta-learning methodology based on meta-unsupervised algorithm for meta-model selection to solve few-shot base-tasks
Humans can solve image classification tasks by learning from a few images and reusing prior-knowledge. In Artificial Intelligence, deep-learning...
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Deep noise mitigation and semantic reconstruction hashing for unsupervised cross-modal retrieval
Cross-modal hashing has attracted much attention due to low storage cost and high retrieval efficiency. Compared with the supervised counterparts,...
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Learning Portrait Drawing with Unsupervised Parts
Translating face photos into portrait drawings takes hours for a skilled artist which makes automatic generation of them desirable. Portrait drawing...
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USIR-Net: sand-dust image restoration based on unsupervised learning
In sand-dust weather, the influence of sand-dust particles on imaging equipment often results in images with color deviation, blurring, and low...
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Unsupervised Deep-Learning Approach for Underwater Image Enhancement
Underwater images often contain color casting and blurriness which reduce the quality. State-of-the-art shows different deep-learning models to...
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Deep learning: systematic review, models, challenges, and research directions
The current development in deep learning is witnessing an exponential transition into automation applications. This automation transition can provide...
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Lifelong learning gets better with MixUp and unsupervised continual representation
Continual learning enables learning systems to adapt to evolving data distributions by sequentially acquiring knowledge from a series of tasks....
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Unsupervised meta-learning via spherical latent representations and dual VAE-GAN
Unsupervised learning and meta-learning share a common goal of enhancing learning efficiency compared to starting from scratch. However,...
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Unsupervised contrastive learning with simple transformation for 3D point cloud data
Though a number of point cloud learning methods have been proposed to handle unordered points, most of them are supervised and require labels for...
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A novel deep unsupervised learning-based framework for optimization of truss structures
In this paper, an efficient deep unsupervised learning (DUL)-based framework is proposed to directly perform the design optimization of truss...
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Deep Learning Foundations and Concepts
This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning...
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Unsupervised Person Re-identification Using Unified Domanial Learning
Recent deep learning-based person re-identification (RE-ID) approaches mainly adopt supervised learning, by which the network is trained with labels...
