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Data Compression

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DTLR-CS: Deep tensor low rank channel cross fusion neural network for reproductive cell segmentation.

PloS one
In recent years, with the development of deep learning technology, deep neural networks have been widely used in the field of medical image segmentation. U-shaped Network(U-Net) is a segmentation network proposed for medical images based on full-conv...

Tree-Structured Data Clustering-Driven Neural Network for Intra Prediction in Video Coding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Intra prediction is a crucial part of video compression, which utilizes local information in images to eliminate spatial redundancy. As the state-of-the-art video coding standard, Versatile Video Coding (H.266/VVC) employs multiple directional predic...

Corruption depth: Analysis of DNN depth for misclassification.

Neural networks : the official journal of the International Neural Network Society
Many large and complex deep neural networks have been shown to provide higher performance on various computer vision tasks. However, very little is known about the relationship between the complexity of the input data along with the type of noise and...

On the compression of neural networks using ℓ-norm regularization and weight pruning.

Neural networks : the official journal of the International Neural Network Society
Despite the growing availability of high-capacity computational platforms, implementation complexity still has been a great concern for the real-world deployment of neural networks. This concern is not exclusively due to the huge costs of state-of-th...

CLPREM: A real-time traffic prediction method for 5G mobile network.

PloS one
Network traffic prediction is an important network monitoring method, which is widely used in network resource optimization and anomaly detection. However, with the increasing scale of networks and the rapid development of 5-th generation mobile netw...

DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification.

Journal of imaging informatics in medicine
Worldwide, the COVID-19 epidemic, which started in 2019, has resulted in millions of deaths. The medical research community has widely used computer analysis of medical data during the pandemic, specifically deep learning models. Deploying models on ...

Fast reconstruction of EEG signal compression sensing based on deep learning.

Scientific reports
When traditional EEG signals are collected based on the Nyquist theorem, long-time recordings of EEG signals will produce a large amount of data. At the same time, limited bandwidth, end-to-end delay, and memory space will bring great pressure on the...

GenCoder: A Novel Convolutional Neural Network Based Autoencoder for Genomic Sequence Data Compression.

IEEE/ACM transactions on computational biology and bioinformatics
Revolutionary advances in DNA sequencing technologies fundamentally change the nature of genomics. Today's sequencing technologies have opened into an outburst in genomic data volume. These data can be used in various applications where long-term sto...

Efficient in Vivo Neural Signal Compression Using an Autoencoder-Based Neural Network.

IEEE transactions on biomedical circuits and systems
Conventional in vivo neural signal processing involves extracting spiking activity within the recorded signals from an ensemble of neurons and transmitting only spike counts over an adequate interval. However, for brain-computer interface (BCI) appli...

VNVC: A Versatile Neural Video Coding Framework for Efficient Human-Machine Vision.

IEEE transactions on pattern analysis and machine intelligence
Almost all digital videos are coded into compact representations before being transmitted. Such compact representations need to be decoded back to pixels before being displayed to humans and - as usual - before being enhanced/analyzed by machine visi...