FUSE-Net: Multi-Scale CNN for NIR Band Prediction from RGB Using GNDVI-Guided Green Channel Enhancement by Gwanghyeong Lee, Deepak Ghimire, Donghoon Kim, Sewoon Cho, Byoungjun Kim, Sunghwan Jeong

“…Hyperspectral imaging (HSI) is a powerful tool for precision imaging tasks such as vegetation analysis, but its widespread use remains limited due to the high cost of equipment and challenges in data acquisition. …”
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Multi-Energy-Microgrid Energy Management Strategy Optimisation Using Deep Learning by Wenyuan Sun, Shuailing Ma, Yufei Zhang, Yingai Jin, Firoz Alam

“…The simulation results suggest that the proposed optimisation model enhances renewable energy use, emissions reductions, microgrid operating costs, and system reliability. The study also reveals that the total system cost and carbon emission cost in the low wind scenario are 283% (2.83 times) and 314% (3.14 times) higher than in the high wind scenario; hence, a significant percentage of renewable energy is needed for microgrid stability.…”
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Resource Optimization for Grid-Connected Smart Green Townhouses Using Deep Hybrid Machine Learning by Seyed Morteza Moghimi, Thomas Aaron Gulliver, Ilamparithi Thirumarai Chelvan, Hossen Teimoorinia

“…The accuracy, efficiency, emissions, and cost are metrics used to evaluate CSGT performance. …”
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Lightweight Indoor Positioning System Based on Multiple Self-Learning Features and Key Frame Classification by C. Wang, K. Bi, B. Zhao, M. Li, Y. Chen, S. Tao, J. Yang

“…This method offers the benefits of low cost and does not require additional hardware installation. …”
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Detecting Vietnam War bomb craters in declassified historical KH-9 satellite imagery by Philipp Barthelme, Eoghan Darbyshire, Dominick V. Spracklen, Gary R. Watmough

“…Bomb craters were manually labeled in a subset of the imagery to train convolutional neural networks (CNNs) for automated crater detection. …”
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Methodology for Occupant Head-Neck Injury Testing in Under-Body Blast Impact Based on Virtual-Real Fusion by Xinge Si, Changan Di, Peng Peng, Cong Xu

“…The high-biofidelity dummy used to evaluate occupant protection under blast conditions is often costly and vulnerable. To address the limitations of low-cost, simplified dummy head–neck structures, which exhibit significant differences in mechanical properties compared to high-biofidelity dummies, a virtual–real fusion-based test method for assessing occupant head–neck injury in under-body blast impacts is proposed. …”
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Research on Underwater Echo Generation Method Based on Small Sample by Chen-yu WANG, Li-wen LIU, Gang LIU, Bo LI, Yun-chuan YANG

“…Combining the characteristics of the echo signal, the study designed and built a convolution unit-based GAN model. Furthermore, an echo signal generation simulation experiment was carried out using the pool experimental test data. …”
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Sliding-Window CNN + Channel-Time Attention Transformer Network Trained with Inertial Measurement Units and Surface Electromyography Data for the Prediction of Muscle Activation an... by Aoyang Bai, Hongyun Song, Yan Wu, Shurong Dong, Gang Feng, Hao Jin

“…SWCTNet integrates IMU and surface electromyography (sEMG) data through sliding window convolution and channel-time attention mechanisms, enabling the efficient extraction of temporal features. …”
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Occupant-Centric Load Optimization in Smart Green Townhouses Using Machine Learning by Seyed Morteza Moghimi, Thomas Aaron Gulliver, Ilamparithi Thirumarai Chelvan, Hossen Teimoorinia

“…A hybrid Long Short-Term Memory and Convolutional Neural Network (LSTM-CNN) model is combined with real-time Internet of Things (IoT) data to predict and optimize energy usage based on occupant behavior and environmental conditions. …”
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Application of ResUNet-CBAM in Thin-Section Image Segmentation of Rocks by Ling Zhao, Huili Zhang, Xianda Sun, Zhaozhuo Ouyang, Chengwu Xu, Xudong Qin

“…The convolutional neural network (CNN) algorithm in deep learning has been widely applied in petroleum geology research both domestically and internationally. …”
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Blockchain-Based Smart Monitoring Framework for Defense Industry by Abdullah Alqahtani, Shtwai Alsubai, Abed Alanazi, Munish Bhatia

“…The proposed method demonstrated the ability to accurately analyze an individual’s anomalous occurrences in activities using a hybrid Convolution Neural Network with Gated Recurrent Units. …”
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Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

“…Additionally, a tiny fully convolutional network architecture has been employed, reducing the number of model parameters and computational costs while maintaining or enhancing performance, which is crucial for real-time medical imaging analysis. …”
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Lightweight Dual-Backbone Detection Transformer for Infrared Insulator Detection by Boyang Zhang, Yanpeng Zhang, Liming Sun

“…Furthermore, the lightweight context gate block (CGBlock) is introduced into the model, improving the model’s spatial awareness and detection accuracy by integrating gated convolution mechanisms and adopting adaptive feature channel weighting strategies. …”
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Toward accurate and scalable rainfall estimation using surveillance camera data and a hybrid deep-learning framework by Fiallos-Salguero Manuel, Soon-Thiam Khu, Jingyu Guan, Mingna Wang

“…The second module integrates depthwise separable convolution (DSC) layers with gated recurrent units (GRU) in a regression model to accurately estimate rainfall intensity using these ROIs. …”
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YOLO-PWSL-Enhanced Robotic Fish: An Integrated Object Detection System for Underwater Monitoring by Lingrui Lei, Ying Tang, Weidong Zhang, Quan Tang, Haichi Hao

“…Therefore, dynamic monitoring of water quality and fish-specific solutions are critical to the growth of fry. Here, a low-cost, small, and real-time monitorable bionic robotic fish based on YOLO-PWSL (PConv, Wise-ShapeIoU, and LGFB) is proposed to achieve intelligent control of aquaculture. …”
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Enhancing Crop Health: Advanced Machine Learning Techniques for Prediction Disease in Palm Oil Tree by Nandy Manish, Kumar Yalakala Dinesh

“…This study has very profound implications—providing a scalable, low cost procedure for observing palm oil tree health. …”
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YOLO-Air: An Efficient Deep Learning Network for Small Object Detection in Drone-Based Imagery by Jigang Qiu, Fangkai Cai, Ning Fu, Yuanfei Yao

“…We propose SECAConv (Squeeze-Excitation Convolution with Attention), which enhances the feature representation of small objects through dynamic weight allocation and channel attention mechanisms. …”
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Detecting heavy trucks from mobile phone trajectories using image-based behavioral representations and deep learning models by Franco Basso, Félix des Rotours, Tomás Maldonado, Raúl Pezoa, Mauricio Varas

“…By employing Call Detail Records (CDR) and introducing an image-inspired architecture, the study uses Convolutional Neural Networks (CNN) to model the microscopic behavioral patterns of mobile devices. …”
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Deep-Learning Techniques Applied for State-Variables Estimation of Two-Mass System by Grzegorz Kaczmarczyk, Radoslaw Stanislawski, Marcin Kaminski

“…The calculations are performed for three deep neural structures based on the Convolutional Neural Network (CNN) and the long short-term memory (LSTM). …”
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Digital Twin Network-Based 6G Self-Evolution by Yuhong Huang, Mancong Kang, Yanhong Zhu, Na Li, Guangyi Liu, Qixing Wang

“…To realize the future shots, we propose a long-term hierarchical convolutional graph attention model for cost-effective network predictions, a conditional hierarchical graph neural network for strategy generation, and methods for efficient small-to-large-scale interactions. …”
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