ACO-Based Neural Network to Enhance the Efficiency of Network Controllability of Temporal Networks by Jie Zhang, Ling Ding, Peyman Arebi

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A Crowd Density Detection Algorithm for Tourist Attractions Based on Monitoring Video Dynamic Information Analysis by Lina Li

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A Hybrid Deep Learning-Based Network for Photovoltaic Power Forecasting by Altaf Hussain, Zulfiqar Ahmad Khan, Tanveer Hussain, Fath U Min Ullah, Seungmin Rho, Sung Wook Baik

“…Renewable energy generation resources, particularly photovoltaics (PVs), are considered as a clean source of energy but are highly complex, volatile, and intermittent in nature making their forecasting challenging. …”
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Improved Deep Feature Learning by Synchronization Measurements for Multi-Channel EEG Emotion Recognition by Hao Chao, Liang Dong, Yongli Liu, Baoyun Lu

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A Mountain Summit Recognition Method Based on Improved Faster R-CNN by Yueping Kong, Yun Wang, Song Guo, Jiajing Wang

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Prediction of Future State Based on Up-To-Date Information of Green Development Using Algorithm of Deep Neural Network by Liyan Sun, Li Yang, Junqi Zhu

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Exudate Detection for Diabetic Retinopathy Using Pretrained Convolutional Neural Networks by Muhammad Mateen, Junhao Wen, Nasrullah Nasrullah, Song Sun, Shaukat Hayat

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Exploration of Temperature-Dependent Thermal Conductivity and Diffusion Coefficient for Thermal and Mass Transportation in Sutterby Nanofluid Model over a Stretching Cylinder by Rabeeah Raza, Muhammad Sohail, Thabet Abdeljawad, Rahila Naz, Phatiphat Thounthong

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Orchestrated Platform for Cyber-Physical Systems by Róbert Lovas, Attila Farkas, Attila Csaba Marosi, Sándor Ács, József Kovács, Ádám Szalóki, Botond Kádár

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Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning by Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu

“…To solve these problems, deep learning has been proposed in recent years to exploit multiple layers of nonlinear information processing for unsupervised self-learning of features. …”
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Multichannel Deep Attention Neural Networks for the Classification of Autism Spectrum Disorder Using Neuroimaging and Personal Characteristic Data by Ke Niu, Jiayang Guo, Yijie Pan, Xin Gao, Xueping Peng, Ning Li, Hailong Li

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Real-Time Road Crack Mapping Using an Optimized Convolutional Neural Network by M-Mahdi Naddaf-Sh, SeyedSaeid Hosseini, Jing Zhang, Nicholas A. Brake, Hassan Zargarzadeh

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Technology and Security Analysis of Cryptocurrency Based on Blockchain by Chao Yu, Wenke Yang, Feiyu Xie, Jianmin He

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A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

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Efficient guided inpainting of larger hole missing images based on hierarchical decoding network by Xiucheng Dong, Yaling Ju, Dangcheng Zhang, Bing Hou, Jinqing He

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Assessing the interactions between time series signals using weighted horizontal visibility graphs by Arya Teymourlouei, James Reggia, Rodolphe Gentili

“…The visibility graph algorithm is used to map recorded time series signals to complex networks. Individual timepoints are treated as nodes, and edges are formed by some criterion of visibility between data points. …”
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Multi-granularity feature intersection learning for visible-infrared person re-identification by Sixian Chan, Jie Wang, Jiaao Cui, Jie Hu, Zhuorong Li, Jiafa Mao

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Hierarchical Disturbance Propagation Mechanism and Improved Contract Net Protocol for Satellite TT&C Resource Dynamic Scheduling by Zhiqing Xiang, Yi Gu, Xinwei Wang, Guohua Wu

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A novel method for distracted driving behaviors recognition with hybrid CNN-BiLSTM-AM model by Dengfeng Zhao, Haojie Li, Zhijun Fu, Bao Ma, Fang Zhou, Chaohui Liu, Wenbin He

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A lightweight vision transformer with weighted global average pooling: implications for IoMT applications by Huiyao Dong, Igor Kotenko, Shimin Dong

“…To tackle this issue, we introduce LightAMViT, a lightweight attention mechanism-enhanced ViT, which incorporates K-means clustering layers to reduce the computational complexity of the self-attention matrix, along with an optimized global average pooling layer that leverages all stacked attention block outputs, each weighted by learnable parameters. …”
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