Developments in image processing using deep learning and reinforcement learning
The growth in the volume of data generated, consumed, and stored, which is estimated to
exceed 180 zettabytes in 2025, represents a major challenge both for organizations and for …
exceed 180 zettabytes in 2025, represents a major challenge both for organizations and for …
Skin disease diagnosis with deep learning: A review
Skin cancer is one of the most threatening diseases worldwide. However, diagnosing skin
cancer correctly is challenging. Recently, deep learning algorithms have emerged to …
cancer correctly is challenging. Recently, deep learning algorithms have emerged to …
Federated learning: A survey on enabling technologies, protocols, and applications
This paper provides a comprehensive study of Federated Learning (FL) with an emphasis
on enabling software and hardware platforms, protocols, real-life applications and use …
on enabling software and hardware platforms, protocols, real-life applications and use …
Automatic detection of citrus fruit and leaves diseases using deep neural network model
A Khattak, MU Asghar, U Batool, MZ Asghar… - IEEE …, 2021 - ieeexplore.ieee.org
Citrus fruit diseases are the major cause of extreme citrus fruit yield declines. As a result,
designing an automated detection system for citrus plant diseases is important. Deep …
designing an automated detection system for citrus plant diseases is important. Deep …
A survey on federated learning in data mining
B Yu, W Mao, Y Lv, C Zhang… - … Reviews: Data Mining and …, 2022 - Wiley Online Library
Data mining is a process to extract unknown, hidden, and potentially useful information from
data. But the problem of data island makes it arduous for people to collect and analyze …
data. But the problem of data island makes it arduous for people to collect and analyze …
Deep learning for fast MR imaging: A review for learning reconstruction from incomplete k-space data
Magnetic resonance imaging is a powerful imaging modality that can provide versatile
information. However, it has a fundamental challenge that is time consuming to acquire …
information. However, it has a fundamental challenge that is time consuming to acquire …
Optimized levy flight model for heart disease prediction using CNN framework in big data application
Cardiac disease is one of the most complex diseases globally. It affects the lives of humans
critically. It is essential for accurate and timely diagnosis to treat heart failure and prevent the …
critically. It is essential for accurate and timely diagnosis to treat heart failure and prevent the …
Emerging trends in fast MRI using deep-learning reconstruction on undersampled k-space data: a systematic review
Magnetic Resonance Imaging (MRI) is an essential medical imaging modality that provides
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …
excellent soft-tissue contrast and high-resolution images of the human body, allowing us to …
Advances of deep learning in electrical impedance tomography image reconstruction
T Zhang, X Tian, XC Liu, JA Ye, F Fu, XT Shi… - … in Bioengineering and …, 2022 - frontiersin.org
Electrical impedance tomography (EIT) has been widely used in biomedical research
because of its advantages of real-time imaging and nature of being non-invasive and …
because of its advantages of real-time imaging and nature of being non-invasive and …
One-dimensional convolutional neural network (1D-CNN) image reconstruction for electrical impedance tomography
X Li, R Lu, Q Wang, J Wang, X Duan, Y Sun… - Review of scientific …, 2020 - pubs.aip.org
In recent years, due to the strong autonomous learning ability of neural network algorithms,
they have been applied for electrical impedance tomography (EIT). Although their imaging …
they have been applied for electrical impedance tomography (EIT). Although their imaging …