Advancements of Deep Learning Model-Based Rehabilitation Training System by Xu Chiyu

“…Another study classified the output layers of shoulder pain rehabilitation using IMU sensors with multiple training programs for different patients wearing IMUs. IMU sensors for rehabilitation training that requires some time to analyze data and feedback data, there are more efficient studies that promote finger movement by giving patients robotic gloves to wear and propose a hand rehabilitation system thus helping stroke survivors with active rehabilitation. …”
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Explainable Offline‐Online Training of Neural Networks for Parameterizations: A 1D Gravity Wave‐QBO Testbed in the Small‐Data Regime by Hamid A. Pahlavan, Pedram Hassanzadeh, M. Joan Alexander

“…Abstract There are different strategies for training neural networks (NNs) as subgrid‐scale parameterizations. …”
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Towards Understanding the Analysis, Models, and Future Directions of Sports Social Networks by Zhongbo Bai, Xiaomei Bai

“…Thirdly, we present and compare different sports social network models that have been used for sports social network analysis, modeling, and prediction. …”
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Generate vector graphics of fine-grained pattern based on the Xception edge detection. by Anqi Chen, Yicui Peng, Meng Li, Hao Chen, Chang Liu, Jinrong Hu, Xiang Wen, Guo Huang

“…We firstly adopt appropriate pre-processing methods, improved adaptive median filtering(IAMF) and non-local mean for the two different types of Qiang embroidery patterns to reduce image noise. …”
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Generative Adversarial Network for Damage Identification in Civil Structures by Zahra Rastin, Gholamreza Ghodrati Amiri, Ehsan Darvishan

“…Most of the proposed methods employ supervised algorithms that require data from different damaged states of a structure in order to monitor its health conditions. …”
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Assessment of Driver Stress using Multimodal wereable Signals and Self-Attention Networks by Pavan Kaveti, Ganapathy Nagarajan

“…Electrocardiogram (ECG) signals (256 Hz) and respiration (RESP) signals (128 Hz) were obtained from ten subjects using textile electrodes while driving in different scenarios, namely normal driving and phone usage (calling). …”
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Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection. by Hongjie Yan, Vivens Mubonanyikuzo, Temitope Emmanuel Komolafe, Liang Zhou, Tao Wu, Nizhuan Wang

“…The proposed Hybrid-RViT model integrates the pre-trained convolutional neural network (ResNet-50) with the Vision Transformer (ViT) to classify brain MRI images across different stages of AD. …”
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AI-Driven Solutions for Early Detection of Plant Diseases by Saha Laboni, Lalmawipuii R.

“…A CNN model is developed and trained in this research on a large annotated dataset of high-resolution plant images from different agricultural environments of healthy and diseased plants. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…The classification resulting from this model yielded high accuracy with robust results for different attack scenarios. Results reflect the potential superiority of the given model in detecting DDoS attacks. …”
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Text classification model of rare earths patents based on ERNE-CAB-CNN by Liao Liefa, Shi Lijiao

“…Combined with ERNIE and Convolutional Neural Network (CNN), an innovative model ERNE-CAB-CNN for rare earth patent text classification is constructed. …”
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A Deep Learning Approach Toward Analyzing the Cross-Lingual Acoustic-Phonetic Similarities in Multilingual Speech Emotion Recognition by Syeda Tamanna Alam Monisha, Sadia Sultana

“…The experimental results reveal that the models can recognize emotions of multiple language speech of the same linguistic family better than language speech from different families. The DCNN model achieved the highest multilingual emotion recognition accuracy of 83% for Indo-Aryan languages, 79% for Germanic languages, and 73% when both language families were combined. …”
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Universal slip detection of robotic hand with tactile sensing by Chuangri Zhao, Yang Yu, Zeqi Ye, Ziyang Tian, Yifan Zhang, Ling-Li Zeng

“…Second, according to the principle of deep double descent, we designed a lightweight universal slip detection convolutional network for different grasp types (USDConvNet-DG) to classify grasp states (no-touch, slipping, and stable grasp). …”
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TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification. by Huiqing Wang, Huajun Wang, Linfen Wu

“…Meanwhile, the transformer-based spectral feature extraction module (TSFEM) was designed by combining the different characteristics of remote sensing images and considering the problem of orderliness of the sequence between hyperspectral image (HSI) channels. …”
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Cross-attention swin-transformer for detailed segmentation of ancient architectural color patterns by Lv Yongyin, Yu Caixia

“…The results highlight the model's ability to generalize well across different tasks and provide robust segmentation, even in challenging scenarios. …”
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ReLU, Sparseness, and the Encoding of Optic Flow in Neural Networks by Oliver W. Layton, Siyuan Peng, Scott T. Steinmetz

“…The present study investigates the influence of different activation functions—ReLU, leaky ReLU, GELU, and Mish—on the accuracy, robustness, and encoding properties of convolutional neural networks (CNNs) and multi-layer perceptrons (MLPs) trained to estimate self-motion from optic flow. …”
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Advances in Online Grain Quality Assessment: Near-Infrared Spectroscopic Modeling and Transfer Strategies by CUI Chen-hao, FAN Chen

“…This review summarizes the application of NIR spectroscopy in online grain quality inspection, systematically outlining the development from traditional linear modeling (e.g., partial least squares regression), nonlinear modeling (e.g., support vector machines, artificial neural networks) to deep learning methods (e.g., convolutional neural networks). It focuses on the strategies, challenges, and latest advances of model transfer techniques in addressing issues such as instrument differences, environmental changes, and sample diversity, including calibration transfer with and without standards. …”

Occupational Therapy Practice Based on New-Generation Information Technology for Employee Emotion Analysis and Management by Yueyuan Cheng

“…There are also significant differences in emotion and work enthusiasm among employees with different educational backgrounds and positions. …”
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Identification of cucumber leaf diseases using deep learning and small sample size for agricultural Internet of Things by Jingyao Zhang, Yuan Rao, Chao Man, Zhaohui Jiang, Shaowen Li

“…To overcome this shortcoming, one approach, based on small sample size and deep convolutional neural network, was proposed for conducting the recognition of cucumber leaf diseases under field conditions. …”
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EST-STFM: An Efficient Deep-Learning-Based Spatiotemporal Fusion Method for Remote Sensing Images by Qiyuan Zhang, Xiaodan Zhang, Chen Quan, Tong Zhao, Wei Huo, Yuanchen Huang

“…By integrating images with different spatial and temporal characteristics, it is possible to generate remote sensing data with enhanced detail and frequency. …”
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Fault Diagnosis Method for UHVDC Transmission Based on Deep Learning under Cloud-Edge Architecture by Shihao Zhou, Benren Pan, Dongbin Lu, Yiming Zhong, Guannan Wang

“…It has the highest diagnosis accuracy under different fault types, and its performance is better than the other three comparison methods.…”
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