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An unsupervised opinion summarization model fused joint attention and dictionary learning
Unsupervised opinion summarization is the technique of automatically generates summaries without gold reference, and the summaries that reflects...
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SUShe: simple unsupervised shadow removal
Shadow removal is an important problem in computer vision, since the presence of shadows complicates core computer vision tasks, including image...
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Maximizing conditional independence for unsupervised domain adaptation
Unsupervised domain adaptation (UDA) studies how to transfer a learner from a labeled source domain to an unlabeled target domain with different...
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Analysis of CoI Presence Indicators in a Moodle Forum Using Unsupervised Learning Techniques
This paper presents a study that uses unsupervised machine learning techniques to analyse CoI presence indicators (Social Presence, Teacher Presence...
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CovSumm: an unsupervised transformer-cum-graph-based hybrid document summarization model for CORD-19
The number of research articles published on COVID-19 has dramatically increased since the outbreak of the pandemic in November 2019. This absurd...
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UTDRM: unsupervised method for training debunked-narrative retrieval models
A key task in the fact-checking workflow is to establish whether the claim under investigation has already been debunked or fact-checked before. This...
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Contrastive learning for unsupervised sentence embeddings using negative samples with diminished semantics
Unsupervised learning has made significant progress in recent years, driven by advancements in contrastive learning. However, current methods for...
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Optimized multi-scale affine shape registration based on an unsupervised Bayesian classification
Here, we intend to introduce an efficient, robust curve alignment algorithm with respect to the group of special affine transformations of the plane...
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Saliency-based dual-attention network for unsupervised video object segmentation
This paper solves the task of unsupervised video object segmentation (UVOS) that segments the objects of interest through the entire videos without...
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Face recognition for human identification through integration of complex domain unsupervised and supervised frameworks
Human identification can be performed through various available biometric traits such as the face, iris, fingerprint, ECG, gait, and ear. Among them,...
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A context-aware unsupervised predictive maintenance solution for fleet management
We deal with the problem of predictive maintenance (PdM) in a vehicle fleet management setting following an unsupervised streaming anomaly detection...
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Supervised and Unsupervised Learning
As we discussed in the last few chapters, supervised and unsupervised learning are two primary approaches to machine learning. At its core, machine...
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Unsupervised Clustering
Unsupervised clustering is useful for automated segregation of participants, grou** of entities, or cohort phenoty**. Such derived computed...
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Variational auto encoder fused with Gaussian process for unsupervised anomaly detection
The unsupervised anomaly detection in high-dimensional and complex settings poses a formidable challenge. To tackle the challenges associated with...
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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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Per-class curriculum for Unsupervised Domain Adaptation in semantic segmentation
Accurate training of deep neural networks for semantic segmentation requires a large number of pixel-level annotations of real images, which are...
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Source Code Clone Detection Using Unsupervised Similarity Measures
Assessing similarity in source code has gained significant attention in recent years due to its importance in software engineering tasks such as...
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Unsupervised Domain Adaptation for Cross-domain Histopathology Image Classification
Unsupervised domain adaptation (UDA) methods have made remarkable progress in histopathological image analysis and various cancer diagnosis domains....
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Hierarchical modal interaction balance cross-modal hashing for unsupervised image-text retrieval
As multimedia technologies advance, untagged image-text data processing has become central in cross-modal retrieval. However, current methods often...
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Unsupervised deep learning of bright-field images for apoptotic cell classification
The classification of apoptotic and living cells is significant in drug screening and treating various diseases. Conventional supervised methods...
