Machine learning has shown utility in detecting patterns within large, unstructured, and
complex datasets. One of the promising applications of machine learning is in precision …

Collective behavior provides a framework for understanding how the actions and properties
of groups emerge from the way individuals generate and share information. In humans …

High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

The rapid advancements in machine learning, graphics processing technologies and the
availability of medical imaging data have led to a rapid increase in the use of deep learning …

This study aimed to produce a robust real-time pear fruit counter for mobile applications
using only RGB data, the variants of the state-of-the-art object detection model YOLOv4, and …

Deep learning has huge potential for accurate disease prediction with neuroimaging data,
but the prediction performance is often limited by training-dataset size and computing …

It is important to detect breast cancer as early as possible. In this manuscript, a new
methodology for classifying breast cancer using deep learning and some segmentation …

Abstract Human Action Recognition (HAR) is a challenging task used in sports such as
volleyball, basketball, soccer, and tennis to detect players and recognize their actions and …

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at
empowering people's capabilities by means of digital environments that are sensitive …

In general, most of the existing convolutional neural network (CNN)-based deep-learning
models suffer from spatial-information loss and inadequate feature-representation issues …