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Search results for: neural network
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1. Biometric Identification Advances: Unimodal to Multimodal Fusion of Face, Palm, and Iris Features
Year: 2024, Volume: 24, Number: 1
... fusion [7]. In identification and deep convolutional neural networks (CNNs) the field of biometric feature ... techniques include sensor-level fusion, feature-level fusion, wavelet transform networks (WTN) for face and iris match-score-level fusion ... irises, as well as deep convolutional neural networks neural network (CNN) and support vector classifier (SVC ...
Year: 2024, Volume: 24, Number: 1
... the information in the discourse. Based on the artificial neural networks. definitions and theories related to the seven ... are mainly focused on the detection of fake like social networks. It is adaptable to social media information on ... , the algorithm combines human factors based on text and network quality (such as consistency of and user perception ...
Year: 2024, Volume: 24, Number: 1
... . 165 renewable power generation and electric vehicles," Neural. Comput. pp. 374 – 406, ... ) in discharging capabilities of plug-in hybrid electric vehicles power networks has been considered as an effective (PHEVs) ... PHEVs can deliver power back to the an external electricity network. In order to model the power grid during ...
Year: 2024, Volume: 24, Number: 1
... feed forward and an EDS is explained by using a neural network PID for a enhanced sliding mode control of ... . 98-103. vehicle by torque balance," Mobile Networks and Applications, pp. 1- doi: ... /ICMECH.2004.1364419 7, 2019. doi:10.1007/s11036-019-01365-w [8] Y. C. Chang, ...
Year: 2023, Volume: 23, Number: 4
... learning models — Decision Tree (DT), Artificial Neural resistant to adversarial attacks. A random subspace Network ... detection. Adaptive adversaries who comprehend the infrastructure of computer networks. The administrators of underlying principles of ML techniques ... Engineering Volume 23, Number 4, 2023 A Robust Network Intrusion Detection System Using Random Forest Based Random Subspace ...
6. Transformer Core Saturation Fault Analysis using Current Sensor Signals and Thermal Image Features
Year: 2023, Volume: 23, Number: 4
... Resolution wavelet- Deep faults. Signal analysis techniques are applied in CT signals Convolutional Neural Network. Energy band-based values from current sensor signal and current sensor thermal image ... extract relevant information regarding inrush current Haralick features are used for differentiating transformer and harmonics [4]. Fault is detected using classification of core-based and load-based faults. ...
Year: 2023, Volume: 23, Number: 4
... 23, Number 4, 2023 Transfer Learning Based Convolutional Neural Network for Classification of Remote Sensing Images Meena Prakash ... are shown monitoring etc., Presently, Convolutional Neural Networks in Fig. 1. (CNN) which ... deep learning based methods are successfully employed for classification problems due to its flexible Machine learning is concerned with mapping ...
Year: 2023, Volume: 23, Number: 3
... aims to make the system information by building a graph neural network of two modalities and then perform inter-modal fusion ... video. The next cross-modal interaction module fuses the neural networks [20-21] or based on dual-stream networks features ... Volume 23, Number 3, 2023 Video Moment Localization Network Based on Text Multi-semantic Clues Guidance Guangli WU, ...
Year: 2023, Volume: 23, Number: 3
... Saglam, S. A. Kalogirou, "Artificial neural network- they overlapped with each other, with ... . Huang, J. H. Chen, "Neural-network-based the array was operated at this point. The ... each PV the best results from the algorithm, the network must be system should be redefined. trained many ...
Year: 2023, Volume: 23, Number: 3
... referred to as "traffic prediction," which can neural networks. mitigate several health issues caused by traffic ... . Also, it can provide alternative paths to traffic jams, saving the I. INTRODUCTION citizens' time ... real-time data to make a short-term learning models or neural network architectures for time prediction of traffic flow during morning ...
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