AIMC Topic: Data Compression
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Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning.
Sensors (Basel, Switzerland)
Jun 7, 2021
Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of var...
QTTNet: Quantized tensor train neural networks for 3D object and video recognition.
Neural networks : the official journal of the International Neural Network Society
Jun 5, 2021
Relying on the rapidly increasing capacity of computing clusters and hardware, convolutional neural networks (CNNs) have been successfully applied in various fields and achieved state-of-the-art results. Despite these exciting developments, the huge ...
Which GAN? A comparative study of generative adversarial network-based fast MRI reconstruction.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
May 10, 2021
Fast magnetic resonance imaging (MRI) is crucial for clinical applications that can alleviate motion artefacts and increase patient throughput. -space undersampling is an obvious approach to accelerate MR acquisition. However, undersampling of -space...
Progressive Transmission of Medical Images via a Bank of Generative Adversarial Networks.
Journal of healthcare engineering
Apr 28, 2021
The healthcare sector is currently undergoing a major transformation due to the recent advances in deep learning and artificial intelligence. Despite a significant breakthrough in medical imaging and diagnosis, there are still many open issues and un...
Small Network for Lightweight Task in Computer Vision: A Pruning Method Based on Feature Representation.
Computational intelligence and neuroscience
Apr 17, 2021
Many current convolutional neural networks are hard to meet the practical application requirement because of the enormous network parameters. For accelerating the inference speed of networks, more and more attention has been paid to network compressi...
Impact of image compression on deep learning-based mammogram classification.
Scientific reports
Apr 12, 2021
Image compression is used in several clinical organizations to help address the overhead associated with medical imaging. These methods reduce file size by using a compact representation of the original image. This study aimed to analyze the impact o...
Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Apr 12, 2021
In this paper, we aim to address issues of (1) joint spatial-temporal modeling and (2) side information injection for deep-learning based in-loop filter. For (1), we design a deep network with both progressive rethinking and collaborative learning me...
Classification of COVID-19 by Compressed Chest CT Image through Deep Learning on a Large Patients Cohort.
Interdisciplinary sciences, computational life sciences
Feb 9, 2021
Corona Virus Disease (COVID-19) has spread globally quickly, and has resulted in a large number of causalities and medical resources insufficiency in many countries. Reverse-transcriptase polymerase chain reaction (RT-PCR) testing is adopted as biops...
Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks.
IEEE transactions on neural networks and learning systems
Feb 4, 2021
Channel pruning is an effective technique that has been widely applied to deep neural network compression. However, many existing methods prune from a pretrained model, thus resulting in repetitious pruning and fine-tuning processes. In this article,...
Recognition of Abnormal Chest Compression Depth Using One-Dimensional Convolutional Neural Networks.
Sensors (Basel, Switzerland)
Jan 27, 2021
When the displacement of an object is evaluated using sensor data, its movement back to the starting point can be used to correct the measurement error of the sensor. In medicine, the movements of chest compressions also involve a reciprocating movem...
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