Deep learning classification of drainage crossings based on high-resolution DEM-derived geomorphological information by Michael Edidem, Bill Xu, Ruopu Li, Di Wu, Banafsheh Rekabdar, Guangxing Wang

“…Although HRDEM-derived geomorphological features have been identified to enhance feature extraction in other hydrography applications, the contributions of these features to drainage crossing image classification have yet to be sufficiently investigated. …”
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A Fault Diagnosis Model for Rotating Machinery Using VWC and MSFLA-SVM Based on Vibration Signal Analysis by Lei You, Wenjie Fan, Zongwen Li, Ying Liang, Miao Fang, Jin Wang

“…As demonstrated by the results, the VWC method is efficient in extracting vibration signal features of rotating machinery. Based on the extracted features, we further compare our classification method with other three fault classification methods, i.e., backpropagation neural network (BPNN), artificial chemical reaction optimization algorithm (ACROA-SVM), and SFLA-SVM. …”
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“Locality – Adaptation” Research of Hydropower Resettlement Communities in the Jinsha River Basin: A Case Study of Ludila Hydropower Station by Fang WANG, Zhuoqi LI, Haoyi XU, Jiaqi YAN

“…At the settlement scale, the Mask Region-based Convolutional Neural Network (Mask R-CNN) deep learning model is utilized to identify architectural spatial features, categorizing three typical building types: traditional pitched-roof buildings, uniformly planned flat-roof buildings, and color steel plate-modified structures. …”
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Constructing segmentation method for wheat powdery mildew using deep learning by Hecang Zang, Hecang Zang, Congsheng Wang, Qing Zhao, Qing Zhao, Jie Zhang, Jie Zhang, Junmei Wang, Guoqing Zheng, Guoqing Zheng, Guoqiang Li, Guoqiang Li

“…Finally, in the deep bottleneck of Swin-Unet network, ResNet network layers are used to increase the expressive power of feature. …”
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Driver and Path Detection through Time-Series Classification by Mario Luca Bernardi, Marta Cimitile, Fabio Martinelli, Francesco Mercaldo

“…The proposed feature model is exploited using a time-series classification approach based on a multilayer perceptron (MLP) network to evaluate their effectiveness for the goals listed above. …”
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Nonlinear Fluctuations in the Cryptocurrency Market: The Modern Approaches to Analysis and Forecasting by Kochorba Valeriia Yu.

“…The author demonstrates evolution from simple linear models to complex neural networks that better account for the nonlinear nature of the market. …”
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Travel Time Probability Prediction Based on Constrained LSTM Quantile Regression by Hao Li, Zijian Wang, Xiantong Li, Hua Wang, Yongxing Man, Jinyu Shi

“…Travel time reliability assessment has been widely used in recent years to evaluate the performance of transportation networks and measure the operation level of transportation systems. …”
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3D Reconstruction With Spherical Cameras by Yan Cui, Qingling Chang, Qiang Liu, Xin Yang, Yajiang Huang, Shichao Chen, Fei Ren, Didier Stricker

“…Experimental results show that our 3DMAP has achieved good evaluation scores and visual effects.…”
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Monitoring of an Electromechanical Prototype Material for Environmental Parameters Using IoT by P. Bharat Siva Varma, Kothapalli Phani Varma, V. Anjani Kranthi, Anusha Rudraraju, Nalla Nandakishore

“…The article’s research was focused on an IoT electronic device and a web platform. A major feature of this electronic device is that its Internet connectivity is achieved using the TCP/IP protocol, an integrated feature of the Shield Ethernet board stacked on top of the Arduino mega board.…”
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Metabolic, transcriptomic, and proteomic adaptations in pancreatic ductal adenocarcinoma-patient derived xenograft models across serial passages by Pengfei Guo, Haizong Fang, Han Shi, Junrong Zhang, Ge Song, Chongjiu Fan, Xinyu Qiu, Xianchao Lin, Shi Wen, Jianghua Feng, Heguang Huang, Tianhong Teng

“…A gene-protein interaction network was constructed to identify functional modules across passages. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…Then, joint spatial-spectral features were extracted by 3D convolutional neural network. …”
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Advanced 3D Artistic Image Generation with VAE-SDFCycleGAN by Dorcas Oladayo Esan, Pius Adewale Owolawi, Chunling Tu

“…To produce 3D artistic images from 2D image that considerably improves scalability and visual quality, this research integrates innovative variational autoencoder signed distance function, cycle generative adversarial network (VAE-SDFCycleGAN). The proposed method feeds a single 2D image into the network to produce a mesh-based 3D shape. …”
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Anamnestic, clinical, and dermoscopic predictors of malignancy in melanocytic lesions with peripheral globules: a retrospective study by Enrico Zelin, Vanessa Mazzoletti, Jessica Paladin, Andrea Corio, Raffaele Dante Caposiena Caro, Giulia Bazzacco, Enzo Errichetti, Nicola Di Meo, Iris Zalaudek

“…The secondary aim was to describe the frequency of these features. We conducted a retrospective cross-sectional observational study, evaluating anamnestic, clinical, and dermoscopic features of MLPGs excised at the Dermatology Clinic of Trieste, Italy (January 2019-June 2023). …”
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Research on image generation technology based on deep learning by Li Jinchen

“…Deep learning can automatically learn the intrinsic features of images， reaching the goal of generating high-quality images by utilizing multi-layer neural network models. …”
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Acoustic cues for person identification using cough sounds by Van-Thuan Tran, Ting-Hao You, Wei-Ho Tsai

“…The training process incorporates a hybrid loss function that combines supervised contrastive (SC) learning and cross-entropy (CE) loss to enhance feature discrimination. We systematically evaluated multiple acoustic representations, including MFCCs and spectrograms, to identify the most suitable features. …”
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ScaleViM-PDD: Multi-Scale EfficientViM with Physical Decoupling and Dual-Domain Fusion for Remote Sensing Image Dehazing by Hao Zhou, Yalun Wang, Wanting Peng, Xin Guan, Tao Tao

“…Furthermore, they typically rely on spatial features while neglecting crucial frequency domain information, resulting in incomplete feature representation. …”
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The analysis of motion recognition model for badminton player movements using machine learning by Xuanmin Zhu, Lizhi Liu, Jingshuo Huang, Genyan Chen, Xi Ling, Yanshuo Chen

“…A badminton stroke recognition method based on Quantum Convolutional Neural Network (QCNN) is proposed. It is then compared with traditional Support Vector Machines (SVM) and Convolutional Neural Network (CNN). …”
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Advances to IoT security using a GRU-CNN deep learning model trained on SUCMO algorithm by Amit Sagu, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, Piyush Kumar Shukla, Mohd Asif Shah

“…The CNN is used to extract the spatial features from the network data, where on the other hand GRUs used for capturing the temporal dependencies. …”
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Hierarchical Semi-Supervised Representation Learning for Cyber Physical Social Intelligence by Na Song, Jing Yang, Xuemei Fu, Xiangli Yang, Ying Xie, Shiping Wang

“…These features are fused to obtain a shared feature. Simultaneously, a learnable graph neural network captures global topology using a graph structure-level reconstruction loss. …”
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GCSA-SegFormer: Transformer-Based Segmentation for Liver Tumor Pathological Images by Jingbin Wen, Sihua Yang, Weiqi Li, Shuqun Cheng

“…The proposed network was evaluated on a liver dataset and the publicly available ICIAR 2018 BACH dataset. …”
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