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A Comparative Study on the Evaluation of k-mer Indexing in Genome Sequence Compression
Low-cost and faster next-generation sequencing (NGS) technology generates huge sequence data for living organisms in the terabyte range. Storing,...
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A novel video compression model based on GPU virtualization with CUDA platform using bi-directional RNN
The exponential increase of superfluous video content across the web applications has provoked the evolution of proficient video compression...
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A Hybrid Model for Video Compression Based on the Fusion of Feature Compression Framework and Multi-object Tracking Network
This paper proposes a video compression algorithm which bases on the combination of feature compression framework and multi-object tracking network....
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Low power high speed FPGA design of lossless medical image compression using optimal deep neural network
Medical image compression is vital for preserving image quality and optimizing storage and transmission in healthcare facilities. FPGA design faces...
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Membership inference attacks against compression models
With the rapid development of artificial intelligence, privacy threats are already getting the spotlight. One of the most common privacy threats is...
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Research and Development of Data Compression Methods Based on Neural Networks
This article discusses a neural network-based compression algorithm using error-correcting codes. The use of this algorithm has a number of...
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Picture quality and compression analysis of multilevel legendre wavelet transformation based image compression technique
A novel lossy RGB (Red, Green, Blue) colour still image compression algorithm is proposed. The intended method introduces Legendre wavelet-based...
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An enhanced AMBTC for color image compression using color palette
Digital image has been used in various fields as an essential carrier. Many color images have been constantly produced since their more realistic...
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Improved discrete Tchebichef transform approximations for efficient image compression
In recent years, the Discrete Tchebichef Transform (DTT) has gained popularity as a signal processing tool for image and video compression due to its...
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Compression through extraction of learned parameters from images in de-correlated image space
Image compression is a class of algorithms that reduces the storage space requirement for a digital image. Lossy image compression techniques achieve...
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A Complex-Valued Neural Network Based Robust Image Compression
Recent works on learned image compression (LIC) based on convolutional neural networks (CNNs) have achieved great improvement with superior...
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Metaheuristic-based energy-aware image compression for mobile app development
The widely applied JPEG standard has undergone recent efforts using population-based metaheuristic (PBMH) algorithms to optimise quantisation tables...
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A Method for Data Compression and Personal Information Suppressing in Columnar Databases
Data privacy and security is the need of the hour. The importance elevates further when we submit the data over a network. It is very easy to extract...
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A deep learning-based compression and classification technique for whole slide histopathology images
This paper presents an autoencoder-based neural network architecture to compress histopathological images while retaining the denser and more...
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Weighted Burrows–Wheeler Compression
A weight-based dynamic compression method has recently been proposed, which is especially suitable for the encoding of files with locally skewed...
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Learning Accurate Performance Predictors for Ultrafast Automated Model Compression
In this paper, we propose an ultrafast automated model compression framework called SeerNet for flexible network deployment. Conventional...
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Use of Neural Networks and Decision Trees in Compression of 2D and 3D Digital Signals
AbstractThe article considers a compression framework for 2D/3D digital signals, including digital images and hyperspectral data. A compression...
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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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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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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...