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Topic Deduplication and Model Compression
There are two critical issues when using the trained topic models: the redundancy of topics and the high computational costs for topic inference....
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Dynamic data resha** for 3D mesh animation compression
Effective compression of 3D mesh animation data has been increasingly used in a variety of multimedia systems including virtual reality, gaming,...
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LUT-LIC: Look-Up Table-Assisted Learned Image Compression
Image compression is indispensable in many visual applications. Recently, learned image compression (LIC) using deep learning has surpassed...
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3DP Code-Based Compression and AR Visualization for Cardiovascular Palpation Training
This paper introduces an augmented reality (AR) visualisation based on the three-dimensional palpation code (3DP code) to enhance palpation training...
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ECG compression based on empirical mode decomposition and tunable-Q wavelet transform with validation using heartbeat classification
In telemedicine-based healthcare system, such as cardiac health monitoring system, large amount of data needs to be stored and transferred. This...
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Parallel Lossy Compression for Large FASTQ Files
In this paper we present a parallel version for the algorithm BFQzip, we introduced in [Guerrini et al., BIOSTEC – BIOINFORMATICS 2022], that...
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Progressive image compression for Gaussian mixture model quartile intervals
In this paper, we proposed a novel deep image coding and decoding model for GMMQI (Gaussian mixture model quartile intervals, GMMQI) and a variable...
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Dynamic Neural Networks for Adaptive Implicit Image Compression
Compression with Implicit Neural Presentations (COIN) is a neural network image compression method based on multilayer perceptron (MLP). COIN encodes...
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Optimization of microscopy image compression using convolutional neural networks and removal of artifacts by deep generative adversarial networks
Nowadays, microscopy images are significant in medical research and clinical studies. However, storage and transmission of data such as microscopy...
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ROI and Non-ROI Image Compression Using Optimal Zero Tree Wavelet and Enhanced Convolutional Neural Network for MRI Images
Medical imaging systems generate enormous amounts of information that place a heavy burden on storage and transmission. As a result, image data...
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Improved ECG signal compression quality using bat algorithm
Recently, electrocardiogram (ECG) data has gained significant importance not only for the medical context but also for purposes related to the...
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MPEG Video-Based Point Cloud Compression (V-PCC) Standard
To achieve efficient compression for 3D dynamic point cloud sequences, MPEG has developed video-based point cloud compression (V-PCC) standard....
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Attention-based variable-size feature compression module for edge inference
Artificial intelligence has made significant breakthroughs in many fields, especially with the broad deployment of edge devices, which provides...
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A compression-based memory-efficient optimization for out-of-core GPU stencil computation
A code for out-of-core stencil computation manages data that exceeds the memory capacity of a GPU. However, such a code necessitates frequent data...
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EARN: toward efficient and robust JPEG compression artifact reduction
JPEG is one of the most widely used lossy image compression algorithms, but artifacts are generated during compression. Various artifact reduction...
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A distributed prediction–compression-based mechanism for energy saving in IoT networks
Nowadays, the number of Internet of things (IoT) devices has rapidly increased due to their increasing use in different real-world applications. The...
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Mixture autoregressive and spectral attention network for multispectral image compression based on variational autoencoder
Multispectral images, with their unique three-dimensional characteristics, require specialized spatial-spectral feature extraction modules to achieve...
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Compression of electrocardiogram signals using compressive sensing technique based on curvelet transform toward medical applications
Electrocardiogram (ECG) signals can be monitored from many patients based on healthcare systems. To enhance these systems, the ECG signals should be...
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Intelligent Image Compression Using Traffic Scene Analysis
The quantity of images generated at the edge of the Cloud is growing year-on-year, which puts an increasing strain on existing telecommunications...
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Segmentation based medical image compression of brain magnetic resonance images using optimized convolutional neural network
Image compression plays a crucial role in the field of medical imaging, including Magnetic Resonance Imaging (MRI). The MRI images are typically...
