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 …

This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Abstract Machine-learning models for medical tasks can match or surpass the performance
of clinical experts. However, in settings differing from those of the training dataset, the …

In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …

Self-supervised pretraining followed by supervised fine-tuning has seen success in image
recognition, especially when labeled examples are scarce, but has received limited attention …

Simple Summary This paper proposes a deep learning-based skin cancer classification
network (DSCC_Net) that is based on a convolutional neural network (CNN) and …

In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …

Given the tremendous potential and influence of artificial intelligence (AI) and algorithmic
decision‐making (DM), these systems have found wide‐ranging applications across diverse …

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 …