Study on Photovoltaic Plant Site Selection Models Based on Geographic and Environmental Features by RAO Zhi, YANG Zaimin, YANG Xiongping, LI Jiaming, YANG Ping, WEI Zhichu

“…A high-precision prediction framework driven by multiple features was constructed by incorporating environmental and geographical parameters into the model input to enhance the overall performance. …”
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Multi-Biometric Feature Extraction from Multiple Pose Estimation Algorithms for Cross-View Gait Recognition by Ausrukona Ray, Md. Zasim Uddin, Kamrul Hasan, Zinat Rahman Melody, Prodip Kumar Sarker, Md Atiqur Rahman Ahad

“…Subsequently, we employed a residual graph convolutional network (ResGCN) to extract features from the generated skeleton data. …”
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A Novel Electrical Load Forecasting Model for Extreme Weather Events Based on Improved Gated Spiking Neural P Systems and Frequency Enhanced Channel Attention Mechanism by Yuanshuo Guo, Jun Wang, Yan Zhong, Tao Wang, Zeyuan Sui

“…This paper proposes a basic framework for future load forecasting researches of sustainable energy systems under extreme weather events and provides new direction for membrane computing model in terms of load forecasting. …”
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TSD-Net: A Traffic Sign Detection Network Addressing Insufficient Perception Resolution and Complex Background by Chengcheng Ma, Chang Liu, Litao Deng, Pengfei Xu

“…By incorporating the C3k2 module and dynamic convolution into the network, the framework achieves enhanced feature extraction flexibility while maintaining high computational efficiency. …”
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Nonlinear time domain and multi-scale frequency domain feature fusion for time series forecasting by Kejiang Xiao, Yefeng Li, Yaning Dong, Wenqi Yang, Binting Yao, Liang Chen

“…At the same time, the framework uses wavelet-based multi-frequency decomposition to clearly divide signals into trend, periodic, and noise components, and enhances feature representation via frequency-domain specific convolutions. …”
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Crude Oil and Hot-Rolled Coil Futures Price Prediction Based on Multi-Dimensional Fusion Feature Enhancement by Yongli Tang, Zhenlun Gao, Ya Li, Zhongqi Cai, Jinxia Yu, Panke Qin

“…With the help of a three-layer convolution neural network structure and adaptive weight fusion strategy, an end-to-end prediction framework is constructed. …”
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SMF-net: semantic-guided multimodal fusion network for precise pancreatic tumor segmentation in medical CT image by Wenyi Zhou, Ziyang Shi, Bin Xie, Fang Li, Jiehao Yin, Yongzhong Zhang, Linan Hu, Lin Li, Yongming Yan, Xiajun Wei, Zhen Hu, Zhengmao Luo, Wanxiang Peng, Xiaochun Xie, Xiaoli Long

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Research on Bearing Fault Diagnosis Method Based on MESO-TCN by Ruibin Gao, Jing Zhu, Yifan Wu, Kaiwen Xiao, Yang Shen

“…To address the issues of information redundancy, limited feature representation, and empirically set parameters in rolling bearing fault diagnosis, this paper proposes a Multi-Entropy Screening and Optimization Temporal Convolutional Network (MESO-TCN). The method integrates feature filtering, network modeling, and parameter optimization into a unified diagnostic framework. …”
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A Transformer-Based Multiscale Difference Enhancement Network for Change Detection by Mengyang Pan, Hang Yang, Chengkang Yu, Mingqing Li, Anping Deng

“…This study establishes TMDENet as a robust framework for high-resolution remote sensing CD, offering significant improvements in both precision and reliability.…”
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IRSD-Net: An Adaptive Infrared Ship Detection Network for Small Targets in Complex Maritime Environments by Yitong Sun, Jie Lian

“…IRSD-Net incorporates a Hierarchical Multi-Kernel Convolution Network (HMKCNet), which employs parallel multi-kernel convolutions and channel division to enhance multi-scale feature extraction while reducing redundancy and memory usage. …”
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OE-YOLO: An EfficientNet-Based YOLO Network for Rice Panicle Detection by Hongqing Wu, Maoxue Guan, Jiannan Chen, Yue Pan, Jiayu Zheng, Zichen Jin, Hai Li, Suiyan Tan

“…To accurately detect rice panicles, this study proposes OE-YOLO, an enhanced framework derived from YOLOv11, incorporating three synergistic innovations. …”
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DSC-SeNet: Unilateral Network with Feature Enhancement and Aggregation for Real-Time Segmentation of Carbon Trace in the Oil-Immersed Transformer by Liqing Liu, Hongxin Ji, Junji Feng, Xinghua Liu, Chi Zhang, Chun He

“…To improve inference speed, a lightweight unilateral feature extraction framework is constructed based on a shallow feature sharing mechanism, which is designed to provide feature input for both semantic path and spatial path. …”
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Smart City Traffic Flow and Signal Optimization Using STGCN-LSTM and PPO Algorithms by Tuxiang Lin, Rongliang Lin

“…This study presents a novel framework that integrates the Spatiotemporal Graph Convolutional Network-Long Short-Term Memory (STGCN-LSTM) model for traffic flow prediction with the Proximal Policy Optimization (PPO) algorithm for dynamic traffic signal control. …”
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Image-based Artificial Intelligence-driven modelling for blank shape optimisation in sheet metal forming by Haosu Zhou, Haoran Li, Yingxue Zhao, Peter R.N. Childs, Nan Li

“…The framework integrates an auto-decoder, serving as a differentiable blank shape generator, a convolutional neural network (CNN)-powered surrogate model for manufacturability evaluation, and an Adam optimiser for automated shape optimisation. …”
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Research on Intelligent Recognition Method of Ground Penetrating Radar Images Based on SAHI by Ruimin Chen, Ligang Cao, Congde Lu, Lei Liu

“…Then, the YOLOv5 model is used for distress detection and the SAHI framework is used in the training and inference stages. …”
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Graph-Based Few-Shot Learning for Synthetic Aperture Radar Automatic Target Recognition with Alternating Direction Method of Multipliers by Jing Jin, Zitai Xu, Nairong Zheng, Feng Wang

“…To address this challenge, we propose a novel few-shot learning (FSL) framework: the alternating direction method of multipliers–graph convolutional network (ADMM-GCN) framework. …”
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A deep learning model for prediction of lysine crotonylation sites by fusing multi-features based on multi-head self-attention mechanism by Yunyun Liang, Minwei Li

“…Finally, a deep learning framework is constructed based on convolutional neural network, bidirectional gated recurrent unit and multilayer perceptron for robust prediction of Kcr sites. …”
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MB-MSTFNet: A Multi-Band Spatio-Temporal Attention Network for EEG Sensor-Based Emotion Recognition by Cheng Fang, Sitong Liu, Bing Gao

“…This paper proposes MB-MSTFNet, a novel framework for EEG emotion recognition. The model constructs a 3D tensor to encode band–space–time correlations of sensor data, explicitly modeling frequency-domain dynamics and spatial distributions of EEG sensors across brain regions. …”
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RMDNet: RNA-aware dung beetle optimization-based multi-branch integration network for RNA–protein binding sites prediction by Jiangbo Zhang, Yunhui Peng, Feifei Cui, Zilong Zhang, Shankai Yan, Qingchen Zhang

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Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification by Aili Wang, Guilong Lei, Shiyu Dai, Haibin Wu, Yuji Iwahori

“…The classification results indicate that the proposed framework, by fully utilizing spatial context information and effectively integrating feature information, significantly outperforms state-of-the-art classification methods.…”
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