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Oleksii Dovhan
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Neural network (NN) model has been widely used in pattern recognition (PR), speech recognition, image processing and other fields, but its application in edge computing (EC) environment faces performance and energy consumption problems. This article first intr…
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Teknologi otentikasi biometrik yang memanfaatkan karakteristik manusia seperti wajah, sidik jari, suara, dan iris mata semakin banyak digunakan untuk seperti wajah, sidik jari, suara, dan iris mata semakin banyak digunakan untuk identifikasi individu. Meskipun…
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Mohammed Alsuhaibani
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The control effectiveness of the all-electric tank stabilizers directly affects the firing accuracy of the tank gun. In order to improve the firing accuracy of the moving tank, this paper proposes a sliding mode control (SMC) strategy using neural network feed…
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Neural Network Models for Feature Extraction and Empirical Thresholding study the combination of neural network models and empirical thresholding methods to improve the procedure for extracting features. For researchers and practitioners working in the fields …
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Credit risk is the most significant risk faced by credit businesses. Currently, various approaches are widely used in credit evaluation. However, methods based on expert knowledge exhibit obvious subjective cognitive bias, while both statistical and machine le…
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Abstract We discuss the concept of probabilistic neural networks with a fixed internal representation being models for machine understanding. Here, ‘understanding’ is interpretted as the ability to map data to an already existing representation which encodes a…
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In addition to its nutritional properties, raisins are also a beneficial food in terms of health due to its vitamins, minerals, antioxidants and phenolic compounds. Turkey ranks first in global raisin production with a production capacity of 24%. Many problems…
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preprints
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Abstract In this brief, we propose a generalized memristor-based neural networks with nonlinear coupling. Based on the set-valued mapping theory, novel Lyapunov indefinite derivative and Memristor theory, the coulped memristor-based neural networks(CMNNs) can …
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Abstract Spiking neural network, consisting of spiking neurons and plastic synapses, is a promising but relatively underdeveloped neural network for neuromorphic computing. Inspired by the human brain, it provides a unique solution for highly efficient data pr…
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Timothy Masters
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Abstract Neural image captioning (NIC) is considered as a primitive problem artificial intelligence (AI) in which creates a connection between computer vision (CV) and natural language processing (NLP). However, recent attribute-based and textual semantic atte…
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Tham Vo
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Abstract Mathematical operations have long been regarded as a sparse, symbolic process in neuroimaging studies. In contrast, advances in artificial neural networks (ANN) have enabled extracting distributed representations of mathematical operations. Recent neu…
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The development of deep learning greatly promotes the progress of speaker verification (SV). Studies show that both convolutional neural networks (CNNs) and dilated time-delay neural networks (TDNNs) achieve advanced performance in text-independent SV, due to …
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