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Gaze estimation using convolutional neural networks
Numerous investigations on gaze estimate techniques for analyzing human behavior have been made in recent years, the majority of which have focused...
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Diagnosis of COVID-19 CT Scans Using Convolutional Neural Networks
Machine learning technology, particularly neural networks, provides useful tools for diagnosing diseases. This study focuses on how convolutional...
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Use of artificial neural networks in architecture: determining the architectural style of a building with a convolutional neural networks
The discussion of "can machines think?" which started with the invention of the modern computer, brought along the question of "can machines design?"...
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A dimensionality reduction approach for convolutional neural networks
The focus of this work is on the application of classical Model Order Reduction techniques, such as Active Subspaces and Proper Orthogonal...
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Learning to rank influential nodes in complex networks via convolutional neural networks
AbstractIdentifying influential nodes is crucial for enhancing information diffusion in complex networks. Several approaches have been proposed to...
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Multi-atlas Graph Convolutional Networks and Convolutional Recurrent Neural Networks-Based Ensemble Learning for Classification of Autism Spectrum Disorders
Autism spectrum disorder (ASD) has an influence on social conversation and interaction, as well as encouraging people to engage in repetitive...
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A revolutionary approach to use convolutional spiking neural networks for robust intrusion detection
In an era dominated by network connectivity, the reliance on robust and secure networks has become paramount. With the advent of 5G and the Internet...
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Convolutional Neural Networks
This chapter presents Convolutional Neural Networks (CNNs). The chapter begins with a review of the convolution equation, and a description of the...
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Convolutional Neural Networks
Artificial neural networks have flourished in recent years in the processing of unstructured data, especially images, text, audio, and speech....
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Convolutional Neural Networks and Architectures
This chapter briefly introduces Convolutional Neural Networks (CNNs). One of the first CNNs is proposed in [41] (known as LeNet) to deal with...
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Symmetry-structured convolutional neural networks
We consider convolutional neural networks (CNNs) with 2D structured features that are symmetric in the spatial dimensions. Such networks arise in...
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Convolutional Neural Networks
Convolutional neural networks are designed to work with grid-structured inputs, which have strong spatial dependencies in local regions of the grid....
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Leveraging Quantum computing for synthetic image generation and recognition with Generative Adversarial Networks and Convolutional Neural Networks
The generation and classification of synthetic images is a challenging and important task in the digital age. Generative Adversarial Networks are...
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Semantic Segmentation of Hyperspectral Imaging Using Convolutional Neural Networks
Abstractusing neural networks in hyperspectral imaging helps to get through the obstruction to solving data analysis, classification, and...
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Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction
Spiking neural networks (SNNs) can be used in low-power and embedded systems e.g. neuromorphic chips due to their event-based nature. They preserve...
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MPEG-1 psychoacoustic model emulation using multiscale convolutional neural networks
The Moving Picture Experts Group - 1 (MPEG-1) perceptual audio compression scheme is a successful family of audio codecs described in standard...
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Application of Convolutional Neural Networks for Creation of Photoluminescent Carbon Nanosensor for Heavy Metals Detection
AbstractThe paper presents results of the use of convolutional neural networks for the development of a multimodal photoluminescent nanosensor based...
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Convolutional Neural Networks
Convolutional neural networks (CNNs) are a category of neural networks that can be used to identify spatial patterns in a robust manner. They achieve...
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Convolutional Neural Networks
A series of successful applications of Convolutional Neural Networks (CNNs) in various computer vision competitions in 2011 and 2012 were a major...
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Deforestation rate estimation using crossbreed multilayer convolutional neural networks
Deforestation is an important environmental issue that involves the removal of forests on a large scale, resulting in ecological imbalance and...
