A Novel Two-Stage Deep Learning Model for Network Intrusion Detection: LSTM-AE by Vanlalruata Hnamte, Hong Nhung-Nguyen, Jamal Hussain, Yong Hwa-Kim

Subjects: “…Convolutional neural network…”
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Federated Learning for Decentralized DDoS Attack Detection in IoT Networks by Yaser Alhasawi, Salem Alghamdi

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HistoNeXt: dual-mechanism feature pyramid network for cell nuclear segmentation and classification by Junxiao Chen, Ruixue Wang, Wei Dong, Hua He, Shiyong Wang

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Intelligent prediction method of network performance based on graph neural network by Yijiang LI, Huibiao YE, Renhua XIE, Jiali LOU, Danna ZHUANG, Chuanhuang LI

“…There are some problems in the traditional network performance prediction technology, such as incomplete network state acquisition and poor accuracy of network performance evaluation.Combined with the characteristics of graph neural network learning and reasoning network relational data and the captured global information of the network, on the basis of the current network performance prediction methods, an intelligent prediction method of network performance based on graph neural network was proposed.Aiming at the complex network information, through the research of network system abstraction and network performance modeling, the network information can be transformed into the graph space convolution was used to process the message passing process of graph network nodes to realize the relationship reasoning between network information.The graph neural network model for network performance prediction was studied, and a graph neural network architecture which could deal with traffic matrix, network topology, routing strategy and node configuration was proposed.Finally, the experiments show that the model can better achieve accurate prediction of the network performance including delay, jitter and packet loss rate.…”
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Free-space optical spiking neural network. by Reyhane Ahmadi, Amirreza Ahmadnejad, Somayyeh Koohi

“…In this work, we introduce the pioneering Free-space Optical Deep Spiking Convolutional Neural Network (OSCNN), a novel approach inspired by the computational model of the human eye. …”
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Bearing Defect Detection with Unsupervised Neural Networks by Jianqiao Xu, Zhaolu Zuo, Danchao Wu, Bing Li, Xiaoni Li, Deyi Kong

“…Sample preprocessing algorithm based on normalized sample symmetry of bearing is adopted to greatly increase the number of samples. Two different convolutional neural networks, supervised networks and unsupervised networks, are tested separately for the bearing defect detection. …”
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Application of Deep Learning to Identify Flutter Flight Testing Signals Parameters and Analysis of Real F-18 Flutter Flight Test Data by Sami Abou-Kebeh, Roberto Gil-Pita, Manuel Rosa-Zurera

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Correction: Khalid et al. Real-Time Plant Health Detection Using Deep Convolutional Neural Networks. <i>Agriculture</i> 2023, <i>13</i>, 510 by Mahnoor Khalid, Muhammad Shahzad Sarfraz, Uzair Iqbal, Muhammad Umar Aftab, Gniewko Niedbała, Hafiz Tayyab Rauf

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Metode Deteksi Pokok Pohon Secara Automatis pada Citra Perkebunan Sawit Menggunakan Model Convolutional Neural Network (CNN) pada Perangkat Lunak Sistem Informasi Geografis by Samuel Samuel, Kestrilia Rega Prilianti, Hendry Setiawan, Prasetyo Mimboro

“…Pada penelitian ini didemonstrasikan penggunaan metode Convolutional Neural Network (CNN) dengan arsitektur ResNet-34 dan ResNet-50 untuk membangun model deteksi pokok pohon sawit dari citra UAV perkebunan sawit PTPN IV. …”
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Text analysis of DNS queries for data exfiltration protection of computer networks by Ya. V. Bubnov, N. N. Ivanov

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Micro-Expression Recognition Using Convolutional Variational Attention Transformer (ConVAT) With Multihead Attention Mechanism by Hafiz Khizer Bin Talib, Kaiwei Xu, Yanlong Cao, Yuan Ping Xu, Zhijie Xu, Muhammad Zaman, Adnan Akhunzada

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Comparative analysis of computing platforms for onboard micromodule of provisional image recognition by V. A. Kovalev, D. A. Paulenka, E. V. Snezhko, V. A. Liauchuk, A. A. Kalinovski

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Homology analysis of malware based on graph by Bing-lin ZHAO, Xi MENG, Jin HAN, Jing WANG, Fu-dong LIU

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Enhancing Remote Sensing Semantic Segmentation Accuracy and Efficiency Through Transformer and Knowledge Distillation by Kang Zheng, Yu Chen, Jingrong Wang, Zhifei Liu, Shuai Bao, Jiao Zhan, Nan Shen

Subjects: “…Convolutional neural network (CNN)…”
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SwinInsSeg: An Improved SOLOv2 Model Using the Swin Transformer and a Multi-Kernel Attention Module for Ship Instance Segmentation by Rabi Sharma, Muhammad Saqib, Chin-Teng Lin, Michael Blumenstein

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Leveraging Deep Learning for Real-Time Coffee Leaf Disease Identification by Opeyemi Adelaja, Bernardi Pranggono

Subjects: “…convolutional neural network…”
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A method for improving recall rate of similar image retrieval by using edge enhancement technology by Jingcheng CAO, Jidong ZHANG, Guojie SHI

Subjects: “…convolutional neural network…”
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Design and modeling of a nanocomposite system for demineralization of sweet whey by Mina Rezapour, Mohsen Esmaiili, Mehdi Mahmoudian, Alireza Behrooz Sarand

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Does Using Artificial Intelligence in Citizen Science Support Volunteers’ Learning? An Experimental Study in Ornithology by Khrystyna Pankiv, Laure Kloetzer

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Heterogeneous long-term changes in larch forest and shrubland cover in the Kolyma lowland are not captured by coarser-scale greening trends by Heather Kropp, Michael M Loranty, Howard Epstein, Gerald V Frost, Adam Koplik, Logan T Berner

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