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Classification of COVID-19 in CT Scans using Multi-Source Transfer Learning
[article]
2020
arXiv
pre-print
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In this study, we propose the use of Multi-Source Transfer Learning (MSTL) to improve upon traditional Transfer Learning for the classification of COVID-19 from CT scans. ...
Due to an inherent lack of available COVID-19 CT data, these research efforts have been forced to leverage the use of Transfer Learning. ...
ACKNOWLEDGEMENTS This work was initiated and facilitated by CS 89.20/189 -Data Science for Health (Spring 2020) at Dartmouth College, taught by Professor Temiloluwa Prioleau. ...
arXiv:2009.10474v1
fatcat:ugwqgvpw3vh6rhsw73a7t5qo2e
Soft Attention Based DenseNet Model for Parkinson's Disease Classification Using SPECT Images
2022
Frontiers in Aging Neuroscience
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For visually analyzing the region of interest (ROI) from the images after classification, Soft Attention Maps and feature map representation are used.OutcomesThe model obtains an overall accuracy of 99.2% ...
The most effective imaging modality for detecting the condition is DaTscan, a variety of single-photon emission computerized tomography (SPECT) imaging method. ...
ACKNOWLEDGMENTS We would like to thank the SRM Institute of Science and Technology, the University of Malaya and Xuzhou Medical University Xuzhou for supporting this research. ...
doi:10.3389/fnagi.2022.908143
pmid:35912076
pmcid:PMC9326232
fatcat:l2w32kvho5evzdxvhevr7uaysm
Utilizing Knowledge Distillation in Deep Learning for Classification of Chest X-ray Abnormalities
2020
IEEE Access
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In Table I , results are shown for the six pre-trained deep models used for normal transfer learning (referred to as base training). ...
gradients to better understand our deep learning model's decisionmaking process. ...
doi:10.1109/access.2020.3020802
fatcat:ucyyrx3ijzft3he2kabn7tgqyi
From Shallow to Deep: Compositional Reasoning over Graphs for Visual Question Answering
[article]
2022
arXiv
pre-print
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It is effortless for human but challenging for machines. ...
In order to achieve a general visual question answering (VQA) system, it is essential to learn to answer deeper questions that require compositional reasoning on the image and external knowledge. ...
However, deeper questions commonly cover relationships (e.g. geometric positions or semantic interactions between objects) beyond mere object detection, so we propose the Relate module to transfer node ...
arXiv:2206.12533v1
fatcat:4ipke63dwfcazl4prpl73gd7si
Detection of Early Pneumonia on Individual CT Scans with Dilated Convolutions
2021
International Workshop on Intelligent Information Technologies & Systems of Information Security
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Thus, early diagnosis and detection of this lung disease are crucial in successful treatment and constant monitoring. ...
An effective dilated convolution operation with different rates, combining features of various receptive fields, was utilized to detect and analyze visual deviations in targeted images. ...
For example, the study [6] applied a transfer training method to a 36-layer CNN to effectively classify pneumonia on a small dataset and used gradient-based CAMs to interpret the automated diagnosis ...
dblp:conf/intelitsis/KrakBR21
fatcat:zggrsr56tbe5xekpmqc4eb6xbu
Augmenting Sensor Performance with Machine Learning Towards Smart Wearable Sensing Electronic Systems
2022
Advanced Intelligent Systems
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, carefully designed soft circuits, etc. ...
As an important subset of AI, Machine learning (ML) has already been widely implemented in many fields of ...
is processed in the fusing algorithm (bottom); h) best accuracy was achieved via bioinspired somatosensory-visual (BSV) associated learning algorithm. ...
doi:10.1002/aisy.202100194
fatcat:7ai5exgvsvgb3kro2brldreqpe
Knee Injury Detection Using Deep Learning on MRI Studies: A Systematic Review
2022
Diagnostics
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There are several possible avenues of further exploration of deep learning for improving MRI-based knee injury diagnosis. ...
In recent years, deep-learning-based approaches have monopolized knee injury detection in MRI studies. ...
Deep Learning with Transfer Learning Bien et al. ...
doi:10.3390/diagnostics12020537
pmid:35204625
pmcid:PMC8871256
fatcat:xp7vdedh35exjhakh7qvdzorie
Point-of-Care Diabetic Retinopathy Diagnosis: A Standalone Mobile Application Approach
[article]
2020
arXiv
pre-print
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This approach could be transferred to other areas of medical image classification. ...
Traditional diagnosis of diabetic retinopathy requires trained ophthalmologists and expensive imaging equipment to reach healthcare centres in order to provide facilities for treatment of preventable blindness ...
The axons of the ganglion cells found in the third layer convey the visual information as encoded by the retina to the next synapse point in the visual pathway via the optic nerve. ...
arXiv:2002.04066v1
fatcat:evsa2qfaebcy5jfjgcespdbhoi
ECOVNet: An Ensemble of Deep Convolutional Neural Networks Based on EfficientNet to Detect COVID-19 From Chest X-rays
[article]
2020
arXiv
pre-print
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At first, the open-access large chest X-ray collection is augmented, and then ImageNet pre-trained weights for EfficientNet is transferred with some customized fine-tuning top layers that are trained, ...
This paper proposed an ensemble of deep convolutional neural networks (CNN) based on EfficientNet, named ECOVNet, to detect COVID-19 using a large chest X-ray data set. ...
On the other hand, diagnosis based on chest X-ray appears to be a propitious solution for COVID-19 detection and treatment. ...
arXiv:2009.11850v2
fatcat:w7xkuzap55hxdomqjbit6udfxu
Guest Editorial: Data-Driven Management of Complex Systems Through Plant-Wide Performance Supervision
2021
IEEE Transactions on Industrial Informatics
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The authors have constructed the multilevel monitoring indexes and fault contribution indexes for the visualization of the fault detection and diagnosis [item 2) in the Appendix]. ...
To achieve quality-related root cause diagnosis for nonlinear processes, in "Quality-related root cause diagnosis based on orthogonal kernel principal component regression and transfer entropy [item 5) ...
doi:10.1109/tii.2020.3023259
fatcat:2x44ydldbreqdcyejz5jui7q24
Region Space Guided Transfer Function Design for Nonlinear Neural Network Augmented Image Visualization
2018
Advances in Multimedia
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There is a strong need today for the acquisition of high quality visualization result for various fields, such as biomedical or other scientific field. ...
The noise in the volume data is suppressed effectively and the boundary between materials can be differentiated clearly by the transfer function designed via the modified 2D histogram. ...
The gradient [21, 22] and curve [23, 24] are introduced as the second variable for the twodimensional transfer function. Roettger et al. ...
doi:10.1155/2018/7479316
fatcat:gdetgxn7zbhufb3lzujkmjunmq
Risk Stratification of Lung Nodules Using 3D CNN-Based Multi-task Learning
[chapter]
2017
Lecture Notes in Computer Science
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2017 pre-print arXiv:1704.08797v1 fatcat:pkvwnibrxjeajk72p3lxwqs5fu
In order to address the need for a large amount for training data for CNN, we resort to transfer learning to obtain highly discriminative features. ...
Moreover, we also acquire the task dependent feature representation for six high-level nodule attributes and fuse this complementary information via a Multi-task learning (MTL) framework. ...
Although CT imaging remains the gold standard for lung cancer detection and diagnosis, Computer-Aided Diagnosis (CAD) and quantification tools are often necessary. ...
doi:10.1007/978-3-319-59050-9_20
fatcat:oq23wasdgrggpevudeg5c5a3ei
Front Matter: Volume 10574
2018
Medical Imaging 2018: Image Processing
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Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
soft distance constraint for dual surfaces segmentation in medical images Topological leakage detection and freeze-and-grow propagation for improved CT-based airway segmentation Student beats the teacher ...
Circle-like foreign element detection in chest x-rays using normalized cross-correlation
and unsupervised clustering [10574-66]
10574 1W
Orientation regression in hand radiographs: a transfer learning ...
doi:10.1117/12.2315755
fatcat:jdfbaent6vhu5dwlrqrqt66vce
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review
[article]
2020
arXiv
pre-print
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This is an ever-growing research for the cases where we have very limited or no datasets available and at the same time, the detection/recognition system has human-like characteristics in learning new ...
Therefore, it makes it applicable in real-world scenarios, from developing autonomous vehicles to medical imaging and COVID-19 Chest X-Ray (CXR) based diagnosis. ...
Using soft-OR, the attributes are divided into groups, and the label class from unseen samples is predicted via a soft-AND within these groups. ...
arXiv:2004.14143v2
fatcat:erh6xyog7bb5vofcebkk2zxumm
SSD-KD: A Self-supervised Diverse Knowledge Distillation Method for Lightweight Skin Lesion Classification Using Dermoscopic Images
[article]
2022
arXiv
pre-print
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However, most studies in skin cancer detection keep pursuing high prediction accuracies without considering the limitation of computing resources on portable devices. ...
Over the last few years, computer-aided diagnosis has been rapidly developed and make great progress in healthcare and medical practices due to the advances in artificial intelligence. ...
Knowledge Distillation (KD), proposed as an extended model compression method, can transfer the learned knowledge from a complicated model (the teacher) to a simple model (the student) by sharing the soft ...
arXiv:2203.11490v2
fatcat:lpxi4cku45atbcy62dxwggsv5a
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