AIMC Topic: Data Compression

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S2LIC: Learned image compression with the SwinV2 block, Adaptive Channel-wise and Global-inter attention Context.

Neural networks : the official journal of the International Neural Network Society May 19, 2025
Recently, deep learning technology has been successfully applied in the field of image compression, leading to superior rate-distortion performance. It is crucial to design an effective and efficient entropy model to estimate the probability distribu...
Humans Neural Networks, Computer Attention Data Compression Entropy Algorithms Deep Learning Image Processing, Computer-Assisted
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Near-lossless EEG signal compression using a convolutional autoencoder: Case study for 256-channel binocular rivalry dataset.

Computers in biology and medicine Mar 5, 2025
Electroencephalography (EEG) experiments typically generate vast amounts of data due to the high sampling rates and the use of multiple electrodes to capture brain activity. Consequently, storing and transmitting these large datasets is challenging, ...
Autoencoder Signal Processing, Computer-Assisted Data Compression Humans Neural Networks, Computer Electroencephalography
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Compression-enabled interpretability of voxelwise encoding models.

PLoS computational biology Feb 19, 2025
Voxelwise encoding models based on convolutional neural networks (CNNs) are widely used as predictive models of brain activity evoked by natural movies. Despite their superior predictive performance, the huge number of parameters in CNN-based models ...
Algorithms Brain Computational Biology Humans Neural Networks, Computer Models, Neurological Principal Component Analysis Data Compression
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Deep learning initialized compressed sensing (Deli-CS) in volumetric spatio-temporal subspace reconstruction.

Magma (New York, N.Y.) Feb 1, 2025
OBJECT: Spatio-temporal MRI methods offer rapid whole-brain multi-parametric mapping, yet they are often hindered by prolonged reconstruction times or prohibitively burdensome hardware requirements. The aim of this project is to reduce reconstruction...
Humans Algorithms Brain Brain Mapping Phantoms, Imaging Data Compression Imaging, Three-Dimensional Image Processing, Computer-Assisted Spatio-Temporal Analysis Magnetic Resonance Imaging Deep Learning
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Online ensemble model compression for nonstationary data stream learning.

Neural networks : the official journal of the International Neural Network Society Jan 22, 2025
Learning from data streams that emerge from nonstationary environments has many real-world applications and poses various challenges. A key characteristic of such a task is the varying nature of the underlying data distributions over time (concept dr...
Online Systems Learning Data Compression Humans Neural Networks, Computer Machine Learning Algorithms
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Continual learning with Bayesian compression for shared and private latent representations.

Neural networks : the official journal of the International Neural Network Society Jan 21, 2025
This paper proposes a new continual learning method with Bayesian Compression for Shared and Private Latent Representations (BCSPLR), which learns a compact model structure while preserving the accuracy. In Shared and Private Latent Representations (...
Bayes Theorem Machine Learning Humans Data Compression Algorithms Neural Networks, Computer Learning
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An end-to-end implicit neural representation architecture for medical volume data.

PloS one Jan 3, 2025
Medical volume data are rapidly increasing, growing from gigabytes to petabytes, which presents significant challenges in organisation, storage, transmission, manipulation, and rendering. To address the challenges, we propose an end-to-end architectu...
Algorithms Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Signal-To-Noise Ratio Data Compression Humans Neural Networks, Computer
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LEC-Codec: Learning-Based Genome Data Compression.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
In this paper, we propose a Learning-based gEnome Codec (LEC), which is designed for high efficiency and enhanced flexibility. The LEC integrates several advanced technologies, including Group of Bases (GoB) compression, multi-stride coding and bidir...
Machine Learning Algorithms Deep Learning Genomics Data Compression Genome Humans Neural Networks, Computer
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FlexPoints: Efficient electrocardiogram signal compression for machine learning.

Journal of electrocardiology Nov 12, 2024
The electrocardiogram (ECG) stands out as one of the most frequently used medical tests, playing a crucial role in the accurate diagnosis and treatment of patients. While ECG devices generate a huge amount of data, only a fraction of it holds valuabl...
Data Compression Algorithms Electrocardiography Signal Processing, Computer-Assisted Humans Machine Learning
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Image quality in three-dimensional (3D) contrast-enhanced dynamic magnetic resonance imaging of the abdomen using deep learning denoising technique: intraindividual comparison between T1-weighted sequences with compressed sensing and with a modified Fast 3D mode wheel.

Japanese journal of radiology Nov 6, 2024
PURPOSE: To assess the image quality of a modified Fast three-dimensional (Fast 3D) mode wheel with sequential data filling (mFast 3D wheel) combined with a deep learning denoising technique (Advanced Intelligent Clear-IQ Engine [AiCE]) in contrast-e...
Male Data Compression Middle Aged Image Enhancement Deep Learning Signal-To-Noise Ratio Aged, 80 and over Adult Humans Retrospective Studies Magnetic Resonance Imaging Imaging, Three-Dimensional Female Image Interpretation, Computer-Assisted Abdomen Aged Contrast Media Artifacts
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