AIMC Topic: Data Compression
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High-throughput deep learning variant effect prediction with Sequence UNET.
Genome biology
May 9, 2023
Understanding coding mutations is important for many applications in biology and medicine but the vast mutation space makes comprehensive experimental characterisation impossible. Current predictors are often computationally intensive and difficult t...
Image Classification Based on Light Convolutional Neural Network Using Pulse Couple Neural Network.
Computational intelligence and neuroscience
Mar 14, 2023
Recently, most image classification studies solicit the intervention of convolutional neural networks because these DL-based classification methods generally outperform other methodologies with higher accuracy. However, this type of deep learning net...
Feature flow regularization: Improving structured sparsity in deep neural networks.
Neural networks : the official journal of the International Neural Network Society
Feb 13, 2023
Pruning is a model compression method that removes redundant parameters and accelerates the inference speed of deep neural networks (DNNs) while maintaining accuracy. Most available pruning methods impose various conditions on parameters or features ...
Application of deep learning algorithms in automatic sonographic localization and segmentation of the median nerve: A systematic review and meta-analysis.
Artificial intelligence in medicine
Jan 21, 2023
OBJECTIVE: High-resolution ultrasound is an emerging tool for diagnosing carpal tunnel syndrome caused by the compression of the median nerve at the wrist. This systematic review and meta-analysis aimed to explore and summarize the performance of dee...
Deep Learning-Based Adaptive Compression and Anomaly Detection for Smart B5G Use Cases Operation.
Sensors (Basel, Switzerland)
Jan 16, 2023
The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of netwo...
An application of deep dual convolutional neural network for enhanced medical image denoising.
Medical & biological engineering & computing
Jan 14, 2023
This work investigates the medical image denoising (MID) application of the dual denoising network (DudeNet) model for chest X-ray (CXR). The DudeNet model comprises four components: a feature extraction block with a sparse mechanism, an enhancement ...
A Hardware-Friendly High-Precision CNN Pruning Method and Its FPGA Implementation.
Sensors (Basel, Switzerland)
Jan 11, 2023
To address the problems of large storage requirements, computational pressure, untimely data supply of off-chip memory, and low computational efficiency during hardware deployment due to the large number of convolutional neural network (CNN) paramete...
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...
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...
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...
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