Transfer learning for medical image classification: a literature review
HE Kim, A Cosa-Linan, N Santhanam, M Jannesari… - BMC medical …, 2022 - Springer
Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …
performances on a new task by leveraging the knowledge of similar tasks learned in …
A review on early forest fire detection systems using optical remote sensing
The environmental challenges the world faces nowadays have never been greater or more
complex. Global areas covered by forests and urban woodlands are threatened by natural …
complex. Global areas covered by forests and urban woodlands are threatened by natural …
[HTML][HTML] Neuroprosthesis for decoding speech in a paralyzed person with anarthria
Background Technology to restore the ability to communicate in paralyzed persons who
cannot speak has the potential to improve autonomy and quality of life. An approach that …
cannot speak has the potential to improve autonomy and quality of life. An approach that …
Automated detection of COVID-19 cases using deep neural networks with X-ray images
Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …
China in December 2019, spread rapidly around the world and became a pandemic. It has …
Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study
Abstract The emergence of Coronavirus Disease 2019 (COVID-19) in early December 2019
has caused immense damage to health and global well-being. Currently, there are …
has caused immense damage to health and global well-being. Currently, there are …
Understanding the role of individual units in a deep neural network
Deep neural networks excel at finding hierarchical representations that solve complex tasks
over large datasets. How can we humans understand these learned representations? In this …
over large datasets. How can we humans understand these learned representations? In this …
Classification of COVID-19 patients from chest CT images using multi-objective differential evolution–based convolutional neural networks
Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease
cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR) …
cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR) …
CNN-based transfer learning–BiLSTM network: A novel approach for COVID-19 infection detection
Abstract Coronavirus disease 2019 (COVID-2019), which emerged in Wuhan, China in 2019
and has spread rapidly all over the world since the beginning of 2020, has infected millions …
and has spread rapidly all over the world since the beginning of 2020, has infected millions …
[HTML][HTML] Introduction to machine learning, neural networks, and deep learning
RY Choi, AS Coyner… - … vision science & …, 2020 - iovs.arvojournals.org
Purpose: To present an overview of current machine learning methods and their use in
medical research, focusing on select machine learning techniques, best practices, and deep …
medical research, focusing on select machine learning techniques, best practices, and deep …
Multi-task deep learning based CT imaging analysis for COVID-19 pneumonia: Classification and segmentation
This paper presents an automatic classification segmentation tool for hel** screening
COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess …
COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess …