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A new deep neural network for forecasting: Deep dendritic artificial neural network
Deep artificial neural networks have become a good alternative to classical forecasting methods in solving forecasting problems. Popular deep neural...
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Deep Convolutional Neural Network for Knowledge-Infused Text Classification
Deep neural networks are extensively used in text mining and Natural Language Processing is to enable computers to understand, analyze, and generate...
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Deep neural network-based secure healthcare framework
Healthcare stands out as a critical domain profoundly impacted by Internet of Things (IoT) technology, generating vast data from sensing devices as...
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A Deep Convolutional Spiking Neural Network for embedded applications
Deep neural networks (DNNs) have received a great deal of interest in solving everyday tasks in recent years. However, their computational and energy...
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Background subtraction for video sequence using deep neural network
Background subtraction aims to extract moving objects from a video sequence which is a prerequisite for high-level surveillance video analysis. There...
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Video Anomaly Detection Based on HSOE-FAST Modified Deep Neural Network
In recent times, video surveillance has become indispensable for public security, leveraging computer vision advancements to analyze and comprehend...
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Parameter identifiability of a deep feedforward ReLU neural network
The possibility for one to recover the parameters—weights and biases—of a neural network thanks to the knowledge of its function on a subset of the...
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Prediction and classification of minerals using deep residual neural network
Minerals are in great demand because of their pervasive application in atomic energy and their use as raw materials for other industries. Despite...
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Intrusion detection system: a deep neural network-based concatenated approach
In recent years, the field of information security has seen a substantial rise in the use of approaches that include deep learning. The...
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Modified Deep-Convolution Neural Network Model for Flower Images Segmentation and Predictions
Nowadays, recognition of plant, leaf, and flower images is one of the most challenging issues due to the wide variety of classes on earth, which are...
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Combining graph neural network with deep reinforcement learning for resource allocation in computing force networks
Fueled by the explosive growth of ultra-low-latency and real-time applications with specific computing and network performance requirements, the...
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Deep primitive convolutional neural network for image super resolution
Deep networks have emerged as a dominant solution in many research areas recently. Numerous approaches based on deep networks have been developed for...
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Optimization Driven Spike Deep Belief Neural Network classifier: a deep-learning based Multichannel Spike Sorting Neural Signal Processor (NSP) module for high-channel-count Brain Machine Interfaces (BMIs)
An Optimization Driven Spike Deep Belief Neural Networks is a type of neural network that is inspired by the functioning of the human brain. It is a...
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Coffee Leaf Disease Classification by Using a Hybrid Deep Convolution Neural Network
The most common symptoms of coffee leaf disease are coffee leaf rust, black rot diseases, and brown eye spot. Leaf rust is the first symptom of...
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Hamiltonian deep neural network fostered sentiment analysis approach on product reviews
In recent times, online shop** has become commonly used method for consumers to make purchases and engage in consumption with the rapid advancement...
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A hybrid deep convolutional neural network model for improved diagnosis of pneumonia
Pneumonia is an infection that inflames the air sacs in lungs and is one of the prime causes of deaths under the age of five, all over the world....
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A novel approach for detecting deep fake videos using graph neural network
Deep fake technology has emerged as a double-edged sword in the digital world. While it holds potential for legitimate uses, it can also be exploited...
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A deep neural network for hand gesture recognition from RGB image in complex background
Deep learning research has gained significant popularity recently, finding applications in various domains such as image preprocessing, segmentation,...
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An efficient deep recurrent neural network for detection of cyberattacks in realistic IoT environment
The rapid growth of Internet of Things (IoT) devices has changed human interactions with the environment. IoT networks require specialized defense...
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A novel exploratory hybrid deep neural network to predict breast cancer for mammography based on wavelet features
A drastic rise in the incidence of breast cancer in patients is witnessed as per the new roadmap launched by the World Health Organization in 2023....
