Buscar
Mostrando ítems 11-20 de 1656
Seam Carving Detection Using Convolutional Neural Networks
(Ieee, 2018-01-01)
Deep Learning techniques have been widely used in the recent years, primarily because of their efficiency in several applications, such as engineering, medicine, and data security. Seam carving is a content-aware image ...
Seam carving detection using convolutional neural networks
(2018-08-20)
Deep Learning techniques have been widely used in the recent years, primarily because of their efficiency in several applications, such as engineering, medicine, and data security. Seam carving is a content-aware image ...
Recognition of Plant Diseases Using Convolutional Neural Networks
(ITESO, 2020-02)
Recognition of Plant Diseases Using Convolutional Neural Networks
(ITESO, 2020-02)
Eye-Tracking Signals Based Affective Classification Employing Deep Gradient Convolutional Neural Networks
Utilizing biomedical signals as a basis to calculate the human affective states is an essential issue of affective computing (AC). With the in-depth research on affective signals, the combination of multi-model cognition ...
Multi-label Classification of Panoramic Radiographic Images Using a Convolutional Neural Network
(2020-01-01)
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 ...
Denoising digital breast tomosynthesis projections using convolutional neural networks
(2021-01-01)
The Digital Breast Tomosynthesis (DBT) projections are obtained with low quality, being essential to use denoising methods to increase the quality of the projections. Currently, deep learning methods have become the ...
Two-level genetic algorithm for evolving convolutional neural networks for pattern recognition
(IEEE-Inst Electrical Electronics Engineers, 2021)
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 ...