Extracting Vehicle Trajectories Using Unmanned Aerial Vehicles in Congested Traffic Conditions by Eui-Jin Kim, Ho-Chul Park, Seung-Woo Ham, Seung-Young Kho, Dong-Kyu Kim

“…In this study, we propose and compare two learning-based frameworks for detecting vehicles: the aggregated channel feature (ACF), which is based on human-made features, and the faster region-based convolutional neural network (Faster R-CNN), which is based on data-driven features. …”
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Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics From Surface EMG by Jie Zhang, Yihui Zhao, Fergus Shone, Zhenhong Li, Alejandro F. Frangi, Sheng Quan Xie, Zhi-Qiang Zhang

“…We use the synchronous muscle forces and joint kinematics prediction from surface electromyogram (sEMG) as the exemplar to illustrate the proposed framework. Convolutional neural network (CNN) is employed as the deep neural network to implement the proposed framework. …”
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Particle swarm optimization with YOLOv8 for improved detection performance of tomato plants by Sarah M. Ayyad, Nada M. Sallam, Samah A. Gamel, Zainab H. Ali

“…Thirdly, the proposed framework was compared with many cutting-edge object detection architectures for tomato harvesting, e.g., Convolutional neural network (CNN), Mask R-CNN and color analysis, and other models based on handcrafted features. …”
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Video-Based Detection Infrastructure Enhancement for Automated Ship Recognition and Behavior Analysis by Xinqiang Chen, Lei Qi, Yongsheng Yang, Qiang Luo, Octavian Postolache, Jinjun Tang, Huafeng Wu

“…To bridge the gap, we proposed an ensemble you only look once (YOLO) framework for ship behavior analysis. First, we employed the convolutional neural network in the YOLO model to extract multi-scaled ship features from the input ship images. …”
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Automated Distal Radius and Ulna Skeletal Maturity Grading from Hand Radiographs with an Attention Multi-Task Learning Method by Xiaowei Liu, Rulan Wang, Wenting Jiang, Zhaohua Lu, Ningning Chen, Hongfei Wang

“…The proposed framework consists of two sub-networks: an encoder–decoder structure with attention gates for segmentation and a slight convolutional network for classification. …”
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Robust ensemble classifier for advanced synthetic aperture radar target classification in diverse operational conditions by Noor Rahman, Muzammil Khan, Imran Khan, Jawad Khan, Youngmoon Lee

“…The ensemble framework achieves improved robustness and classification accuracy across varied scenarios. …”
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Emotion-Aware Ensemble Learning (EAEL): Revolutionizing Mental Health Diagnosis of Corporate Professionals via Intelligent Integration of Multi-Modal Data Sources and Ensemble Tech... by Gaurav Yadav, Mohammad Ubaidullah Bokhari, Saleh I. Alzahrani, Shadab Alam, Mohammed Shuaib

“…This research introduces the Emotion-Aware Ensemble Learning (EAEL) framework, a cutting-edge approach designed to revolutionize early mental health diagnosis among corporate professionals. …”
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Multi-Stage Audio-Visual Fusion for Dysarthric Speech Recognition With Pre-Trained Models by Chongchong Yu, Xiaosu Su, Zhaopeng Qian

“…This operation is different from the traditional approach solely based on the movement of lip in audio-visual fusion framework. During the second stage, we proposed to use the AV-HuBERT framework to pre-train the recognition architecture of fusing audio and visual information of the dysarthric speech. …”
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SDA-Mask R-CNN: An Advanced Seabed Feature Extraction Network for UUV by Yao Xiao, Dongchen Dai, Hongjian Wang, Chengfeng Li, Shaozheng Song

“…This paper proposes a novel SDA-Mask R-CNN framework for precise seabed terrain edge feature extraction from Side-Scan Sonar (SSS) images to enhance Unmanned Underwater Vehicle (UUV) perception and navigation. …”
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LLM-Augmented Linear Transformer–CNN for Enhanced Stock Price Prediction by Lei Zhou, Yuqi Zhang, Jian Yu, Guiling Wang, Zhizhong Liu, Sira Yongchareon, Nancy Wang

“…In this study, we propose a novel hybrid deep learning framework that integrates a large language model (LLM), a Linear Transformer (LT), and a Convolutional Neural Network (CNN) to enhance stock price prediction using solely historical market data. …”
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Redundant Path Optimization in Smart Ship Software-Defined Networking and Time-Sensitive Networking Networks: An Improved Double-Dueling-Deep-Q-Networks-Based Approach by Yanli Xu, Songtao He, Zirui Zhou, Jingxin Xu

“…Central to this framework is the introduction of a redundant multipath selection algorithm, which leverages Double Dueling Deep Q-Networks (D3QNs) in conjunction with Graph Convolutional Networks (GCNs). …”
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3D reconstruction for unconstrained image collections using Gaussian Splatting with foundation model by Shuowen Huang, Qingwu Hu, Pengcheng Zhao, Mingyao Ai, Xujie Zhang, Wenwu Ou, Linze Li

“…In this study, we propose the U3GS framework for Gaussian Splatting under unconstrained image collections. …”
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Multimodal Fusion Multi-Task Learning Network Based on Federated Averaging for SDB Severity Diagnosis by Songlu Lin, Renzheng Tang, Yuzhe Wang, Zhihong Wang

“…The proposed framework is built upon a hybrid deep neural architecture that integrates convolutional layers (CNN) for spatial representation, bidirectional GRUs for temporal modeling, and multi-head self-attention for long-range dependency learning. …”
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Edge–Cloud Intelligence for Sustainable Wind Turbine Blade Transportation: Machine-Vision-Driven Safety Monitoring in Renewable Energy Systems by Yajun Wang, Xiaodan Wang, Yihai Wang, Shibiao Fang

“…The framework employs an optimized YOLOv7-Tiny model. It is enhanced with convolutional block attention modules (CBAMs) for feature refinement, CARAFE upsampling for better contextual detail, and bidirectional feature pyramid networks (BiFPNs) for multi-scale object detection. …”
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Hierarchical Transfer Learning with Transformers to Improve Semantic Segmentation in Remote Sensing Land Use by Miaomiao Chen, Lianfa Li

“…Our framework represents multilevel transfer learning, progressing from non-remote sensing classification to coarse classification, then to the refined classification of remote sensing. …”
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Cyberattack Detection Systems in Industrial Internet of Things (IIoT) Networks in Big Data Environments by Abdullah Orman

“…This study proposes an advanced IDS framework integrating machine learning, deep learning, and hybrid models to enhance cybersecurity in IIoT environments. …”
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Multimodal learning for enhanced SPECT/CT imaging in sports injury diagnosis by Zhengzheng Jiang, YaWen Shen

“…Our method introduces a hybrid model combining convolutional neural networks for spatial feature extraction and transformer-based temporal attention for sequential pattern recognition. …”
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Evaluation Model Based on the SGCNiFormer for the Influence of Different Storage Environments on Wheat Quality by Qingchuan Zhang, Zexi Song, Mingwen Bi

“…This integrated method provides a systematic theoretical framework for optimizing storage parameters and offers substantial support for intelligent grain storage management.…”
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FishermaskFormer: Lightweight Remote Sensing Scene Classification With Masked Transformer by Wei Wu, Xianbin Hu, Zhu Li, Xueliang Luo

“…This is aimed at offering a flexible and effective framework for preserving classification accuracy while significantly reducing the complexity. …”
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Forecasting Sales in Live-Streaming Cross-Border E-Commerce in the UK Using the Temporal Fusion Transformer Model by Qi Zhang, Xue Li, Pengbin Gao

“…To address these challenges, we propose a novel sales forecasting framework utilizing the Temporal Fusion Transformer (TFT) model. …”
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