AIMC Topic: Data Compression

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Advanced machine learning algorithms to evaluate the effects of the raw ingredients on flowability and compressive strength of ultra-high-performance concrete.

PloS one Dec 22, 2022
The estimation of concrete characteristics through artificial intelligence techniques is come out to be an effective way in the construction sector in terms of time and cost conservation. The manufacturing of Ultra-High-Performance Concrete (UHPC) is...
Artificial Intelligence Machine Learning Algorithms Data Compression Pharmaceutical Vehicles Compressive Strength
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Verification of delay time and image compression thresholds for telesurgery.

Asian journal of endoscopic surgery Dec 7, 2022
INTRODUCTION: Telerobotic surgery relies on communication lines, causing delays, and video information requires pre-transmission compression. Such delays and video degradation will continue to be unavoidable making communication conditions verificati...
Humans Animals Surgeons Swine Robotics Robotic Surgical Procedures Telemedicine Data Compression
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On Information Plane Analyses of Neural Network Classifiers-A Review.

IEEE transactions on neural networks and learning systems Nov 30, 2022
We review the current literature concerned with information plane (IP) analyses of neural network (NN) classifiers. While the underlying information bottleneck theory and the claim that information-theoretic compression is causally linked to generali...
Neural Networks, Computer Data Compression Information Theory
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Data-Independent Structured Pruning of Neural Networks via Coresets.

IEEE transactions on neural networks and learning systems Nov 30, 2022
Model compression is crucial for the deployment of neural networks on devices with limited computational and memory resources. Many different methods show comparable accuracy of the compressed model and similar compression rates. However, the majorit...
Neural Networks, Computer Algorithms Neurons Data Compression
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SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks.

IEEE transactions on neural networks and learning systems Nov 30, 2022
Deep neural networks include millions of learnable parameters, making their deployment over resource-constrained devices problematic. Sensitivity-based regularization of neurons (SeReNe) is a method for learning sparse topologies with a structure, ex...
Neural Networks, Computer Algorithms Neurons Data Compression
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Learned Gradient Compression for Distributed Deep Learning.

IEEE transactions on neural networks and learning systems Nov 30, 2022
Training deep neural networks on large datasets containing high-dimensional data requires a large amount of computation. A solution to this problem is data-parallel distributed training, where a model is replicated into several computational nodes th...
Neural Networks, Computer Deep Learning Data Compression Entropy
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Deep Learning-Based Synthesized View Quality Enhancement with DIBR Distortion Mask Prediction Using Synthetic Images.

Sensors (Basel, Switzerland) Oct 24, 2022
Recently, deep learning-based image quality enhancement models have been proposed to improve the perceptual quality of distorted synthesized views impaired by compression and the Depth Image-Based Rendering (DIBR) process in a multi-view video system...
Deep Learning Image Enhancement Data Compression
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IIB-CPE: Inter and Intra Block Processing-Based Compressible Perceptual Encryption Method for Privacy-Preserving Deep Learning.

Sensors (Basel, Switzerland) Oct 21, 2022
Perceptual encryption (PE) of images protects visual information while retaining the intrinsic properties necessary to enable computation in the encryption domain. Block-based PE produces JPEG-compliant images with almost the same compression savings...
Algorithms Deep Learning Privacy Computer Security Data Compression
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Perturbation of deep autoencoder weights for model compression and classification of tabular data.

Neural networks : the official journal of the International Neural Network Society Sep 27, 2022
Fully connected deep neural networks (DNN) often include redundant weights leading to overfitting and high memory requirements. Additionally, in tabular data classification, DNNs are challenged by the often superior performance of traditional machine...
Neural Networks, Computer Machine Learning Data Compression Physical Phenomena
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RAt-CapsNet: A Deep Learning Network Utilizing Attention and Regional Information for Abnormality Detection in Wireless Capsule Endoscopy.

IEEE journal of translational engineering in health and medicine Aug 16, 2022
: The emergence of wireless capsule endoscopy (WCE) has presented a viable non-invasive mean of identifying gastrointestinal diseases in the field of clinical gastroenterology. However, to overcome its extended time of manual inspection, a computer a...
Neural Networks, Computer Animals Deep Learning Rats Gastrointestinal Tract Capsule Endoscopy Data Compression
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