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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 ...
Sensitivity and generalized analytical sensitivity expressions for quantitative analysis using convolutional neural networks
(Elsevier Science, 2022-05)
In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; however, ...
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 ...
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 ...
Does Removing Pooling Layers from Convolutional Neural Networks Improve Results?
(2020-09-01)
Due to their number of parameters, convolutional neural networks are known to take long training periods and extended inference time. Learning may take so much computational power that it requires a costly machine and, ...
Analyzing the effect of hyperparameters in a automobile classifier based on convolutional neural networks
(IEEE Computer Society, 2017)
In the recent years the convolutional neural network is used successfully in applications of image classification, due to its deep and hierarchical architecture. The hyper parameters of the convolutional neural networks ...
Deep neural network approaches for Spanish sentiment analysis of short texts
(Springer Verlag, 2018)
Sentiment Analysis has been extensively researched in the last years. While important theoretical and practical results have been obtained, there is still room for improvement. In particular, when short sentences and low ...
Rate-energy-accuracy Optimization Of Convolutional Architectures For Face Recognition
(Academic Press in Elsevier ScienceSan Diego, 2016)
Rate-energy-accuracy Optimization Of Convolutional Architectures For Face Recognition
(ACADEMIC PRESS INC ELSEVIER SCIENCESAN DIEGO, 2016)