AIMC Topic: Data Compression

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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...
Humans Neural Networks, Computer Machine Learning Genomics Data Compression Genome Algorithms Deep Learning
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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 Electrocardiography Signal Processing, Computer-Assisted Machine Learning Algorithms Humans
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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...
Humans Retrospective Studies Aged, 80 and over Adult Male Female Aged Signal-To-Noise Ratio Data Compression Contrast Media Artifacts Imaging, Three-Dimensional Magnetic Resonance Imaging Image Enhancement Abdomen Middle Aged Image Interpretation, Computer-Assisted Deep Learning
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A unified noise and watermark removal from information bottleneck-based modeling.

Neural networks : the official journal of the International Neural Network Society Nov 4, 2024
Both image denoising and watermark removal aim to restore a clean image from an observed noisy or watermarked one. The past research consists of the non-learning type with limited effectiveness or the learning types with limited interpretability. To ...
Signal-To-Noise Ratio Data Compression Humans Algorithms Image Processing, Computer-Assisted Neural Networks, Computer
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Sparse Coding Inspired LSTM and Self-Attention Integration for Medical Image Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Oct 25, 2024
Accurate and automatic segmentation of medical images plays an essential role in clinical diagnosis and analysis. It has been established that integrating contextual relationships substantially enhances the representational ability of neural networks...
Image Processing, Computer-Assisted Data Compression Algorithms Databases, Factual Humans Neural Networks, Computer
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Dual-stage feedback network for lightweight color image compression artifact reduction.

Neural networks : the official journal of the International Neural Network Society Jul 22, 2024
Lossy image coding techniques usually result in various undesirable compression artifacts. Recently, deep convolutional neural networks have seen encouraging advances in compression artifact reduction. However, most of them focus on the restoration o...
Neural Networks, Computer Algorithms Deep Learning Image Processing, Computer-Assisted Humans Data Compression Color Feedback Artifacts
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Joint Dual Feature Distillation and Gradient Progressive Pruning for BERT compression.

Neural networks : the official journal of the International Neural Network Society Jul 17, 2024
The increasing size of pre-trained language models has led to a growing interest in model compression. Pruning and distillation are the primary methods employed to compress these models. Existing pruning and distillation methods are effective in main...
Data Compression Neural Networks, Computer Algorithms Humans
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LD-CSNet: A latent diffusion-based architecture for perceptual Compressed Sensing.

Neural networks : the official journal of the International Neural Network Society Jul 14, 2024
Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging the constraints of the Nyquist-Shannon sampling theorem. This enables high-quality image reconstruction using a minimal number of measurements. Neural Networks' po...
Humans Neural Networks, Computer Diffusion Algorithms Data Compression Image Processing, Computer-Assisted
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Sharing massive biomedical data at magnitudes lower bandwidth using implicit neural function.

Proceedings of the National Academy of Sciences of the United States of America Jul 3, 2024
Efficient storage and sharing of massive biomedical data would open up their wide accessibility to different institutions and disciplines. However, compressors tailored for natural photos/videos are rapidly limited for biomedical data, while emerging...
Biomedical Research Humans Deep Learning Neural Networks, Computer Information Dissemination Data Compression
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Multi-file dynamic compression method based on classification algorithm in DNA storage.

Medical & biological engineering & computing Jun 26, 2024
The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its develo...
DNA Data Compression Machine Learning Algorithms Humans
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