xViTCOS: explainable vision transformer based COVID-19 screening using radiography
Objective: Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19)
across the globe has pushed the health care system in many countries to the verge of …
across the globe has pushed the health care system in many countries to the verge of …
Review on Transfer Learning for Convolutional Neural Network
R Kaur, R Kumar, M Gupta - 2021 3rd International Conference …, 2021 - ieeexplore.ieee.org
Convolutional neural network (CNN) has recently received much interest from researchers
as an image classification technique. CNN requires a lot of data to train a model from …
as an image classification technique. CNN requires a lot of data to train a model from …
Employment of an electronic tongue combined with deep learning and transfer learning for discriminating the storage time of Pu-erh tea
Z Yang, N Miao, X Zhang, Q Li, Z Wang, C Li, X Sun… - Food Control, 2021 - Elsevier
Pu-erh tea is a famous Chinese fermented tea, and its quality and flavor are closely related
to the storage time used for its fermentation. This paper puts forward one method to …
to the storage time used for its fermentation. This paper puts forward one method to …
A review on deep learning applications with semantics
In recent years, improvements in hardware and software which increased the speed of
computing and production of large amounts of data that meet the needs of educational data …
computing and production of large amounts of data that meet the needs of educational data …
Active-learning-incorporated deep transfer learning for hyperspectral image classification
A hyperspectral image (HSI) includes a vast quantity of samples, a large number of bands,
and randomly occurring redundancy. Classifying such complex data is challenging, and its …
and randomly occurring redundancy. Classifying such complex data is challenging, and its …
Multispectral and SAR image fusion based on Laplacian pyramid and sparse representation
Complementary information from multi-sensors can be combined to improve the availability
and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful …
and reliability of stand-alone data. Typically, multispectral (MS) images contain plentiful …
Enhancing convergence speed with feature enforcing physics-informed neural networks using boundary conditions as prior knowledge
M Jahani-Nasab, MA Bijarchi - Scientific Reports, 2024 - nature.com
This research introduces an accelerated training approach for Vanilla Physics-Informed
Neural Networks (PINNs) that addresses three factors affecting the loss function: the initial …
Neural Networks (PINNs) that addresses three factors affecting the loss function: the initial …
Hyperspectral image few-shot classification network based on the earth mover's distance
J Sun, X Shen, Q Sun - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Deep learning has achieved promising performance in hyperspectral image (HSI)
classification. Training deep models usually requires labeling massive HSIs, which …
classification. Training deep models usually requires labeling massive HSIs, which …
Diagnosis of COVID-19 pneumonia based on graph convolutional network
X Liang, Y Zhang, J Wang, Q Ye, Y Liu, J Tong - Frontiers in Medicine, 2021 - frontiersin.org
A three-dimensional (3D) deep learning method is proposed, which enables the rapid
diagnosis of coronavirus disease 2019 (COVID-19) and thus significantly reduces the …
diagnosis of coronavirus disease 2019 (COVID-19) and thus significantly reduces the …
Fast adapting without forgetting for face recognition
Although face recognition has made dramatic improvements in recent years, there are still
many challenges in real-world applications such as face recognition for the elderly and …
many challenges in real-world applications such as face recognition for the elderly and …