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   Articles with "deep clustering" as a keyword



An Improved Deep Clustering Model for Underwater Acoustical Targets

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recommendations! Published in 2017 at "Neural Processing Letters"

DOI: 10.1007/s11063-017-9755-7

Abstract: Hand-craft features and clustering algorithms constitute the main parts of the unsupervised clustering system. Performance of the clustering deteriorates when the assumed probabilistic distribution of the data differs from the true one. This paper introduces… read more here.

Keywords: deep clustering; underwater acoustical; model; clustering model ... See more keywords
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DCSR: Deep clustering under similarity and reconstruction constraints

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recommendations! Published in 2020 at "Neurocomputing"

DOI: 10.1016/j.neucom.2020.06.013

Abstract: Abstract Clustering is a difficult but crucial task in pattern recognition and machine learning. Inherently, clustering methods are always subject to the uncertainty of similarities between samples. To weaken the impact of such uncertainty, we… read more here.

Keywords: reconstruction; clustering similarity; deep clustering; similarity reconstruction ... See more keywords

Deep clustering using 3D attention convolutional autoencoder for hyperspectral image analysis

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recommendations! Published in 2024 at "Scientific Reports"

DOI: 10.1038/s41598-024-54547-2

Abstract: Deep clustering has been widely applicated in various fields, including natural image and language processing. However, when it is applied to hyperspectral image (HSI) processing, it encounters challenges due to high dimensionality of HSI and… read more here.

Keywords: attention convolutional; analysis; deep clustering; hyperspectral image ... See more keywords

Deep Clustering of Remote Sensing Scenes through Heterogeneous Transfer Learning

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recommendations! Published in 2024 at "International Journal of Remote Sensing"

DOI: 10.1080/01431161.2025.2465917

Abstract: ABSTRACT Satellite and aerial imagery is collected at a dizzying rate, but how to best distill this information is often unknown. Classifying images is the most popular approach but requires specifying groups a priori. This… read more here.

Keywords: sensing scenes; clustering remote; deep clustering; scenes heterogeneous ... See more keywords

A noise-robust deep clustering of biomolecular ions improves interpretability of mass spectrometric images

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recommendations! Published in 2023 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btad067

Abstract: Abstract Motivation Mass Spectrometry Imaging (MSI) analyzes complex biological samples such as tissues. It simultaneously characterizes the ions present in the tissue in the form of mass spectra, and the spatial distribution of the ions… read more here.

Keywords: deep clustering; ion images; noise robust; mass ... See more keywords

Deep clustering of bacterial tree images

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recommendations! Published in 2022 at "Philosophical Transactions of the Royal Society B: Biological Sciences"

DOI: 10.1098/rstb.2021.0231

Abstract: The field of genomic epidemiology is rapidly growing as many jurisdictions begin to deploy whole-genome sequencing (WGS) in their national or regional pathogen surveillance programmes. WGS data offer a rich view of the shared ancestry… read more here.

Keywords: deep clustering; clustering bacterial; bacterial tree; comet ... See more keywords

Multi-Head Self-Attention-Based Deep Clustering for Single-Channel Speech Separation

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recommendations! Published in 2020 at "IEEE Access"

DOI: 10.1109/access.2020.2997871

Abstract: Turning attention to a particular speaker when many people talk simultaneously is known as the cocktail party problem. It is still a tough task that remained to be solved especially for single-channel speech separation. Inspired… read more here.

Keywords: attention; separation; deep clustering; self attention ... See more keywords
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Intelligent Anomaly Detection for Large Network Traffic With Optimized Deep Clustering (ODC) Algorithm

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recommendations! Published in 2021 at "IEEE Access"

DOI: 10.1109/access.2021.3068172

Abstract: The availability of an enormous amount of unlabeled datasets drives the anomaly detection research towards unsupervised machine learning algorithms. Deep clustering algorithms for anomaly detection gain significant research attention in this era. We propose an… read more here.

Keywords: deep clustering; anomaly detection; network traffic; clustering ... See more keywords

Robust scRNA-seq Cell Types Identification by Self-Guided Deep Clustering Network

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3394038

Abstract: The emergence of single-cell RNA sequencing (scRNA-seq) has brought to light the critical need for scrutinizing transcriptomes at the individual cellular level with unparalleled precision. A pivotal aspect of scRNA-seq data analysis involves cell identification,… read more here.

Keywords: cell; deep clustering; network; scrna seq ... See more keywords

Deep Clustering With Self-Supervision Using Pairwise Similarities

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2025.3600986

Abstract: Deep clustering incorporates embedding into clustering to find a lower-dimensional space appropriate for clustering. In this paper, we propose a novel deep clustering framework with self-supervision using pairwise data similarities (DCSS). The proposed method consists… read more here.

Keywords: deep clustering; space; supervision using; self supervision ... See more keywords

Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets

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recommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"

DOI: 10.1109/jbhi.2022.3187215

Abstract: Melanoma is a fatal skin cancer that is curable and has dramatically increasing survival rate when diagnosed at early stages. Learning-based methods hold significant promise for the detection of melanoma from dermoscopic images. However, since… read more here.

Keywords: deep clustering; highly imbalanced; triplet loss; triplet ... See more keywords