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   Articles with "visual data" as a keyword



mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations

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recommendations! Published in 2019 at "Nucleic Acids Research"

DOI: 10.1093/nar/gkz1128

Abstract: Abstract Mitochondria participate in metabolism and signaling. They adapt to the requirements of various cell types. Publicly available expression data permit to study expression dynamics of genes with mitochondrial function (mito-genes) in various cell types,… read more here.

Keywords: data mining; expression dynamics; mitochondrial expression; mining platform ... See more keywords

Boosting Business With Machine Learning-Based Automated Visual Data Processing: Results of Finnish Company Interviews

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recommendations! Published in 2020 at "IEEE Access"

DOI: 10.1109/access.2020.2993669

Abstract: Machine Learning (ML) solutions are rapidly evolving and are increasingly capable of performing Automated Visual Data Processing (AVDP) tasks such as visual scene understanding, 3D model reconstruction and automated content generation tasks. We believe that… read more here.

Keywords: business; visual data; data processing; automated visual ... See more keywords

Privacy Aware Affective State Recognition from Visual Data

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3165622

Abstract: Affective state recognition is a key component of any system equipped with emotional awareness and intelligence. The ability of recognizing emotions allows the machine to better understand the user requirements, and guide its decision and… read more here.

Keywords: recognition; visual data; affective state; state recognition ... See more keywords

User-Defined Interactions for Visual Data Exploration With the Combination of Smartwatch and Large Display

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3404876

Abstract: The process of visual analytics is composed of the visual data exploration tasks supporting analytical reasoning. When performing analytical tasks with the interactive visual interfaces displayed by the large screen, physical discomforts such as gorilla-arm… read more here.

Keywords: data exploration; user defined; defined interactions; large display ... See more keywords

FedVisual: Heterogeneity-Aware Model Aggregation for Federated Learning in Visual-Based Vehicular Crowdsensing

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recommendations! Published in 2024 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2024.3456751

Abstract: With the advancement of assisted and autonomous driving technologies, vehicles are being outfitted with an ever-increasing number of sensors. Among these, visible light sensors, or dash-cameras, produce visual data rich in information. Analyzing this visual… read more here.

Keywords: model aggregation; model; federated learning; crowdsensing fedvisual ... See more keywords

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

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recommendations! Published in 2023 at "IEEE MultiMedia"

DOI: 10.1109/mmul.2023.3245919

Abstract: The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Telecommunication Union - Telecommunication Sector (ITU-T)… read more here.

Keywords: visual data; consumption; machine; image coding ... See more keywords

Enhancing Visual Data Completion With Pseudo Side Information Regularization

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2024.3453393

Abstract: Unsupervised image restoration methods relying on a single data source often face challenges in achieving high-quality visual data completion due to the absence of additional supplementary information. This paper presents a novel optimization framework to… read more here.

Keywords: completion; data completion; pseudo side; side information ... See more keywords

Nonlocal Low-Rank Tensor Completion for Visual Data

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recommendations! Published in 2021 at "IEEE Transactions on Cybernetics"

DOI: 10.1109/tcyb.2019.2910151

Abstract: In this paper, we propose a novel nonlocal patch tensor-based visual data completion algorithm and analyze its potential problems. Our algorithm consists of two steps: the first step is initializing the image with triangulation-based linear… read more here.

Keywords: tensor; completion; visual data; low rank ... See more keywords

MDSFE: Multiscale Deep Stacking Fusion Enhancer Network for Visual Data Enhancement

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recommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2022.3222517

Abstract: With the rapid development of visual sensors and artificial intelligence (AI), video/image data has increased dramatically, especially in the era of AI-enabled intelligent transportation. In low-light imaging conditions, however, the camera only captures weak scene-reflected… read more here.

Keywords: visual data; fusion; fusion enhancer; stacking fusion ... See more keywords

Multi-Attention DenseNet: A Scattering Medium Imaging Optimization Framework for Visual Data Pre-Processing of Autonomous Driving Systems

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recommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"

DOI: 10.1109/tits.2022.3145815

Abstract: The vision system is important for almost all kinds of autonomous driving systems. However, visual data interfered by scattering media, such as smoke, haze, water, and other non-uniform media will be degraded seriously, showing the… read more here.

Keywords: visual data; scattering medium; driving systems; attention ... See more keywords

Disentangling the Modes of Variation in Unlabelled Data

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recommendations! Published in 2018 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"

DOI: 10.1109/tpami.2017.2783940

Abstract: Statistical methods are of paramount importance in discovering the modes of variation in visual data. The Principal Component Analysis (PCA) is probably the most prominent method for extracting a single mode of variation in the… read more here.

Keywords: variation; modes variations; variation unlabelled; disentangling modes ... See more keywords