Compared with common deep learning methods (eg, convolutional neural networks),
transfer learning is characterized by simplicity, efficiency and its low training cost, breaking …

The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …

Deep learning techniques, which use a massive technology known as convolutional neural
networks, have shown excellent results in a variety of areas, including image processing …

Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …

Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …

This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and
transfer learning in the context of medical imaging. Medical imaging plays a critical role in …

Deep learning requires a large amount of data to perform well. However, the field of medical
image analysis suffers from a lack of sufficient data for training deep learning models …

Featured Application The proposed intelligent medical system is applicable for a medical
diagnostic system, especially for the diagnosis of diabetic foot ulcer. Abstract One of the …

Transfer learning (TL) has been widely utilized to address the lack of training data for deep
learning models. Specifically, one of the most popular uses of TL has been for the pre …