Deep Learning-Based Multimode Fiber Distributed Temperature Sensing by Luxuan Yang, Xiaoyan Wang, Tong Wu, Huichuan Lin, Songjie Luo, Ziyang Chen, Yongxin Liu, Jixiong Pu

“…The precision of the predicting heating point was less than 1 cm. Different types of MMFs were used in temperature measurements, showing that the accuracy remained quite high. …”
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Predicting steady degradation in ship power system: A deep learning approach based on comprehensive monitoring parameters by Xingshan Chang, Xiaojian Xu, Bohua Qiu, Muheng Wei, Xinping Yan, Jie Liu

“…Addressing the challenge of predicting the SD process, this study introduces the YC2Model, a system‐level predictive method that integrates encoding time slice data to images (ETSD2I) with a convolutional neural network and Transformer. Incorporating the Transformer, in particular, enables the YC2Model to predict the SD state of SPS over extended periods more effectively. …”
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A Deep Curriculum Learning Semi-Supervised Framework for Remote Sensing Scene Classification by Qing Zhang, Jialu Chen, Baohua Yuan

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SeqConv-Net: A Deep Learning Segmentation Framework for Airborne LiDAR Point Clouds Based on Spatially Ordered Sequences by Bin Guo, Chunjing Yao, Hongchao Ma, Jie Wang, Junhao Xu

“…To address this issue, we propose a novel sequence convolution semantic segmentation architecture that integrates Convolutional Neural Networks (CNN) with a sequence-to-sequence (seq2seq) structure, termed SeqConv-Net. …”
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Robust SOH estimation for Li-ion battery packs of real-world electric buses with charging segments by Heng Li, Shilong Zhuo, Yun Zhou, Muaaz Bin Kaleem, Yu Jiang, Fu Jiang

“…The proposed method is validated using approximately four years of operational data from three different types of electric buses. Through cross-validation, the method demonstrates high accuracy, achieving absolute errors below 3% in over 80% of cycle cases. …”
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Enhancing Real Estate Listings Through Image Classification and Enhancement: A Comparative Study by Eyüp Tolunay Küp, Melih Sözdinler, Ali Hakan Işık, Yalçın Doksanbir, Gökhan Akpınar

“…A dataset of 3000 labeled images was utilized to compare different image classification models, including convolutional neural networks (CNNs), VGG16, residual networks (ResNets), and the LLaVA large language model (LLM). …”
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A non-anatomical graph structure for boundary detection in continuous sign language by Razieh Rastgoo, Kourosh Kiani, Sergio Escalera

“…To enhance the model performance, replace the handcrafted feature extractor, and also consider the hand structure in these models, we propose a deep learning-based approach, including a combination of the Graph Convolutional Network (GCN) and the Transformer models, along with a post-processing mechanism for final boundary detection. …”
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Deep Learning‐Based Prediction of Global Ionospheric TEC During Storm Periods: Mixed CNN‐BiLSTM Method by Xiaochen Ren, Biqiang Zhao, Zhipeng Ren, Yan Wang, Bo Xiong

“…In this study, an improved model called Mixed Convolutional Neural Networks (CNN)—Bi‐Long Short Term Memory is proposed for predicting future ionospheric Total Electron Content (TEC). …”
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A comprehensive framework for multi-modal hate speech detection in social media using deep learning by R. Prabhu, V. Seethalakshmi

“…Hence, this research proposes a novel Multi-modal Hate Speech Detection Framework (MHSDF) that combines Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to analyze complex, heterogeneous data streams. …”
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Automated detection of quiet eye durations in archery using electrooculography and comparative deep learning models by Fatma Söğüt, Hüseyin Yanık, Evren Değirmenci, İnci Kesilmiş, Ülkü Çömelekoğlu

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Artificial Intelligence and Hand Hygiene Accuracy: A New Era in Infection Control for Dental Practices by Salwa A. Aldahlawi, Amr H. Almoallim, Ibtesam K. Afifi

“…Material and Method The AI model utilized a pretrained convolutional neural network (CNN) and was fine‐tuned on a custom data set of videos showing dental students performing alcohol‐based hand rub (ABHR) procedures. …”
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Edge-Enhanced GCIFFNet: A Multiclass Semantic Segmentation Network Based on Edge Enhancement and Multiscale Attention Mechanism by Long Chen, Zhiyuan Qu, Yao Zhang, Jingyang Liu, Ruwen Wang, Dezheng Zhang

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Detecting stress parameters in dromedary camels using computer vision by Hiba Moideen, Manar Abu Talib, Nabil Mansour, Shaher Bano Mirza, Ali Bou Nassif, Simon Zerisenay Ghebremeskel, Fouad Lamghari, Yaman Afadar, Takua Mokhamed

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IOT-MDEDTL: IoT Malware Detection based on Ensemble Deep Transfer Learning by Qasim Kadhim, Ahmed Qassem Ali Sharhan Al-Sudani, Inas Amjed Almani, Tawfeeq Alghazali, Hasan Khalid Dabis, Atheer Taha Mohammed, Saad Ghazi Talib, Rawnaq Adnan Mahmood, Zahraa Tariq Sahi, Yaqeen Mezaal

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Improving robotic grasping accuracy through oriented bounding box detection with YOLOv11-OBB by Vo Duy Cong, Le Hoai Phuong

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GM2FFNet: Grouped Multiscale Multiangle Feature Fusion Network With Center Attention for Hyperspectral Image Classification by Junding Sun, Haoxiang Dong, Yanlong Gao, Xiaosheng Wu, Jianlong Wang, Yudong Zhang

“…First, a grouped multiscale extraction module captures and fuses spectral features at different scales using various kernels. Second, a grouped multiangle convolution module extracts features from multiple directions, with an adaptive fusion module further integrating this information. …”
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Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants by Mohamed Farag Taha, Hanping Mao, Samar Mousa, Lei Zhou, Yafei Wang, Gamal Elmasry, Salim Al-Rejaie, Abdallah Elshawadfy Elwakeel, Yazhou Wei, Zhengjun Qiu

“…The results demonstrated that the LSTM outperformed the convolutional neural network (CNN) and multi-class support vector machine (MCSVM) approaches. …”
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PEMETAAN PENGGUNAAN LAHAN SAWAH BERDASARKAN PENDEKATAN EKOLOGI BENTANG LAHANMENGGUNAKAN CITRA PEREKAMAN TUNGGAL by Algi Variski Hasibuan, Projo Danoedoro, Sigit Heru Murti

“…The use of ten optical bands in multispectral classification using the maximum likelihood algorithm and convolutional neural network algorithm resulted in twelve land cover classes. …”
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Facial Beauty Prediction Combining Dual-Branch Feature Fusion With a Stacked Broad Learning System by Junying Gan, Hantian Chen, Wenchao Xu, Huicong Li, Zhenxin Zhuang, Zhen Chen

“…Current models rely on single feature extraction, such as using a single convolutional neural network to extract local feature, failing to capture other potentially more important information contained within facial data and limiting feature diversity. …”
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Unsupervised hyperspectral noise estimation and restoration via interband-invariant representation learning by Zhaozhi Luo, Janne Heiskanen, Xinyu Wang, Yanfei Zhong, Petri Pellikka

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