R-CNN-Based Satellite Components Detection in Optical Images by Yulang Chen, Jingmin Gao, Kebei Zhang

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Lithium-Ion Battery Degradation Based on the CNN-Transformer Model by Yongsheng Shi, Leicheng Wang, Na Liao, Zequan Xu

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Research on Feature Extracted Method for Flutter Test Based on EMD and CNN by Hua Zheng, Zhenglong Wu, Shiqiang Duan, Jiangtao Zhou

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Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm by Dhea Amanda Ramadhan, Dian Ramadhani

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A data Mining Approach using CNN and LSTM to Predict Divorce before Marriage by Touba Torabipour, Safieh Siadat, Hosein Taghavi

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Improving Diabetic Patients Monitoring System Using (NCA-CNN) Algorithm based on loT by Ayas Talib Mohammad, Jaber Parchami

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Optimizing colorectal polyp detection and localization: Impact of RGB color adjustment on CNN performance by Jirakorn Jamrasnarodom, Pharuj Rajborirug, Pises Pisespongsa, Kitsuchart Pasupa

“…Thus, although RGB color adjustment enhances CNN model performance for detecting and localizing colorectal polyps, further research is needed to verify these improvements across diverse datasets and clinical settings. • RGB Color Adjustment: Applied RGB color adjustments to colonoscopic images to enhance the performance of Convolutional Neural Network (CNN) models. • Model Development: Used YOLOv8s for polyp detection and localization, with Bayesian optimization to identify the best RGB adjustments. • Performance Evaluation: Assessed model performance using mAP and F1-scores on both internal and external validation datasets.…”
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Facial Emotion Recognition and Classification Using the Convolutional Neural Network-10 (CNN-10) by Emmanuel Gbenga Dada, David Opeoluwa Oyewola, Stephen Bassi Joseph, Onyeka Emebo, Olugbenga Oluseun Oluwagbemi

“…Emotions can depict the state of health and internal wellbeing of individuals. Facial expression detection has been a hot research topic in the last couple of years. …”
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Advancing Wildlife Protection: Mask R-CNN for Rail Track Identification and Unwanted Object Detection by Istiak Mahmud, Md. Mohsin Kabir, Jungpil Shin, Chayan Mistry, Yoichi Tomioka, M. F. Mridha

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Positioning of the Moving and Static Contacts of the Switch Machine Based on Double-Layer Mask R-CNN by Jiacheng Yin, Zhaomin Lv, Xingjie Chen, Kun Yang

“…The accuracy and robustness of the proposed DLM are verified by the internal image of the switch machine.…”
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Empowering Urdu sentiment analysis: an attention-based stacked CNN-Bi-LSTM DNN with multilingual BERT by Lal Khan, Atika Qazi, Hsien-Tsung Chang, Mousa Alhajlah, Awais Mahmood

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Detection of COVID-19 Using a Pre-trained CNN Model Over Chest X-ray Images by Mohammadreza Behnia, Touba Torabipour, Safieh Siadat

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Classification of Stages 1,2,3 and Preplus, Plus disease of ROP using MultiCNN_LSTM classifier by Ranjana Agrawal, Sucheta Kulkarni, Madan Deshpande, Anita Gaikwad, Rahee Walambe, Ketan V. Kotecha

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A Lightweight CNN-Transformer Implemented via Structural Re-Parameterization and Hybrid Attention for Remote Sensing Image Super-Resolution by Jie Wang, Hongwei Li, Yifan Li, Zilong Qin

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Enhancing plant disease detection through deep learning: a Depthwise CNN with squeeze and excitation integration and residual skip connections by Asadulla Y. Ashurov, Mehdhar S. A. M. Al-Gaashani, Nagwan A. Samee, Reem Alkanhel, Ghada Atteia, Hanaa A. Abdallah, Mohammed Saleh Ali Muthanna

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Towards combining self-organizing maps (SOM) and convolutional neural network (CNN) for improving model accuracy: Application to malaria vectors phenotypic resistance by Komi Mensah Agboka, Elfatih M. Abdel-Rahman, Daisy Salifu, Brian Kanji, Frank T. Ndjomatchoua, Ritter A.Y. Guimapi, Sunday Ekesi, Landmann Tobias

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Intelligent cloud guidance technology based on natural language learning by Renjie TANG, Tao JIANG, Qiaojie YANG

“…The main problems existing in the current guidance system were analyzed.According to the intelligent guidance system researched in the current academic circles,a self-learning system for the disease which based on a large number of patient condition descriptions using a variety of machine learning algorithms was creatively proposed.The platform used Web crawler technology to obtain setting of the international and domestic medical institution departments and a large number of patient descriptions,which form a pathological knowledge base and a disease self-reported knowledge base.At the same time,the algorithm was innovatively constructed to combine the attention model with TextCNN to improve the accuracy of the consultation.…”
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Automatic Evaluation of Internal Combustion Engine Noise Based on an Auditory Model by Kai Liang, Haijun Zhao

“…To improve the accuracy and efficiency of the objective evaluation of noise quality from internal combustion engines, an automatic noise quality classification model was constructed by introducing an auditory model-based acoustic spectrum analysis method and a convolutional neural network (CNN) model. …”
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A Study on the Differences in Optimized Inputs of Various Data-Driven Methods for Battery Capacity Prediction by Kuo Xin, Fu Jia, Byoungik Choi, Geesoo Lee

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Metode Deteksi Pokok Pohon Secara Automatis pada Citra Perkebunan Sawit Menggunakan Model Convolutional Neural Network (CNN) pada Perangkat Lunak Sistem Informasi Geografis by Samuel Samuel, Kestrilia Rega Prilianti, Hendry Setiawan, Prasetyo Mimboro

“…Pada penelitian ini didemonstrasikan penggunaan metode Convolutional Neural Network (CNN) dengan arsitektur ResNet-34 dan ResNet-50 untuk membangun model deteksi pokok pohon sawit dari citra UAV perkebunan sawit PTPN IV. …”
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