AIMC Topic: Data Compression

Clear Filters Showing 61 to 70 of 147 articles

Research on Lung Ultrasound Image Classification Based on Compressed Sensing.

Journal of healthcare engineering Mar 23, 2022
Pneumothorax is a common injury in disaster rescue, traffic accidents, and war trauma environments and requires early diagnosis and treatment. The commonly used X-ray, CT, and other diagnostic instruments are not suitable for rescue sites due to thei...
Humans Neural Networks, Computer Lung Ultrasonography Thorax Data Compression
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Compression of Deep Neural Networks based on quantized tensor decomposition to implement on reconfigurable hardware platforms.

Neural networks : the official journal of the International Neural Network Society Mar 8, 2022
Deep Neural Networks (DNNs) have been vastly and successfully employed in various artificial intelligence and machine learning applications (e.g., image processing and natural language processing). As DNNs become deeper and enclose more filters per l...
Neural Networks, Computer Artificial Intelligence Machine Learning Algorithms Data Compression
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Deep Learning Post-Filtering Using Multi-Head Attention and Multiresolution Feature Fusion for Image and Intra-Video Quality Enhancement.

Sensors (Basel, Switzerland) Feb 10, 2022
The paper proposes a novel post-filtering method based on convolutional neural networks (CNNs) for quality enhancement of RGB/grayscale images and video sequences. The lossy images are encoded using common image codecs, such as JPEG and JPEG2000. The...
Neural Networks, Computer Deep Learning Video Recording Data Compression
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First Gradually, Then Suddenly: Understanding the Impact of Image Compression on Object Detection Using Deep Learning.

Sensors (Basel, Switzerland) Feb 1, 2022
Video surveillance systems process high volumes of image data. To enable long-term retention of recorded images and because of the data transfer limitations in geographically distributed systems, lossy compression is commonly applied to images prior ...
Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Data Compression
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PCA driven mixed filter pruning for efficient convNets.

PloS one Jan 24, 2022
Deployment of the deep neural networks (DNNs) on resource-constrained devices is a challenging task due to their limited memory and computational power. In most cases, the pruning techniques do not prune the DNNs to full extent and redundancy still e...
Neural Networks, Computer Software Models, Statistical Principal Component Analysis Datasets as Topic Data Compression
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Joint segmentation and classification of breast masses based on ultrasound radio-frequency data and convolutional neural networks.

Ultrasonics Jan 14, 2022
In this paper, we propose a novel deep learning method for joint classification and segmentation of breast masses based on radio-frequency (RF) ultrasound (US) data. In comparison to commonly used classification and segmentation techniques, utilizing...
Humans Neural Networks, Computer Retrospective Studies Diagnosis, Differential Ultrasonography, Mammary Data Compression Breast Diseases Radio Waves
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Telemetry Data Compression Algorithm Using Balanced Recurrent Neural Network and Deep Learning.

Computational intelligence and neuroscience Jan 10, 2022
Telemetric information is great in size, requiring extra room and transmission time. There is a significant obstruction of storing or sending telemetric information. Lossless data compression (LDC) algorithms have evolved to process telemetric data e...
Neural Networks, Computer Algorithms Deep Learning Data Compression Telemetry
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Research on Video Quality Evaluation of Sparring Motion Based on BPNN Perception.

Computational intelligence and neuroscience Dec 27, 2021
The quality of boxing video is affected by many factors. For example, it needs to be compressed and encoded before transmission. In the process of transmission, it will encounter network conditions such as packet loss and jitter, which will affect th...
Neural Networks, Computer Algorithms Motion Perception Data Compression
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LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks.

Neural networks : the official journal of the International Neural Network Society Dec 2, 2021
LOBSTER (LOss-Based SensiTivity rEgulaRization) is a method for training neural networks having a sparse topology. Let the sensitivity of a network parameter be the variation of the loss function with respect to the variation of the parameter. Parame...
Neural Networks, Computer Data Compression
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Evaluation of Deep Neural Network Compression Methods for Edge Devices Using Weighted Score-Based Ranking Scheme.

Sensors (Basel, Switzerland) Nov 12, 2021
The demand for object detection capability in edge computing systems has surged. As such, the need for lightweight Convolutional Neural Network (CNN)-based object detection models has become a focal point. Current models are large in memory and deplo...
Neural Networks, Computer Pressure Data Compression
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