Convolutional Neural Networks (CNNs) have set the state-of-the-art in many computer vision tasks in recent years. For this type of model, it is common to have millions of parameters to train, commonly requiring large ...

Filter selection in convolutional neural networks aims at finding the most important filters in a convolutional layer, with the goal of reducing computational costs and needed storage, as well as understanding the networks’ ...

Deep learning-based approaches have been paramount in recent years, mainly due to their outstanding results in several application domains, ranging from face and object recognition to handwritten digit identification. ...

OBJECTIVES: During the COVID-19 pandemic, convolutional neural networks (CNNs) have been used in clinical medicine (eg, X-rays classification). Whether CNNs could inform the epidemiology of COVID-19 classifying street ...

The aim of Neuroevolution is to nd neural networks and convolutional neural network (CNN) architectures automatically through evolutionary algorithms. A crucial problem in neuroevolution is search time, since multiple ...

Dentistry is one of the areas which mostly present potential for application of machine learning techniques, such as convolutional neural networks (CNNs). This potential derives from the fact that several of the typical ...

Deep Learning has achieved state-of-the-art results in several domains, such as image processing, natural language processing, and audio processing. To accomplish such results, it uses neural networks with several processing ...

Employee safety is paramount in the manufacturing industry to ensure their well-being and protection. Technological advancements, particularly convolutional neural networks (CNN), have significantly enhanced this safety ...