Examine the Prediction Error of Ride-Hailing Travel Demands with Various Ignored Sparse Demand Effects by Zhiju Chen, Kai Liu, Tao Feng

“…To obtain the spatiotemporal characteristics of the travel demand, three hexagon-based deep learning models (H-CNN-LSTM, H-CNN-GRU, and H-ConvLSTM) are compared by setting various threshold values. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…The hybrid CNN-LSTM has extraction capabilities regarding both the spatial and temporal features of network traffic data, showing highly efficient performance. …”
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3D Simulation Design and Application of Traditional Hanfu Based on Internet of Things by Li Lin, Wen Gan

“…The reliability of IoT technology also improves the accuracy of CNN methods in predicting Hanfu eigenvalues. The largest prediction error is only 2.84%. …”
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Image-Based Detection and Classification of Malaria Parasites and Leukocytes with Quality Assessment of Romanowsky-Stained Blood Smears by Jhonathan Sora-Cardenas, Wendy M. Fong-Amaris, Cesar A. Salazar-Centeno, Alejandro Castañeda, Oscar D. Martínez-Bernal, Daniel R. Suárez, Carol Martínez

“…Parasite detection used high-intensity region selection and adaptive bounding boxes, followed by a custom convolutional neural network (CNN) for candidate identification. A second CNN classified parasites into trophozoites, schizonts, and gametocytes. …”
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Liquid-based cytological diagnosis of pancreatic neuroendocrine tumors using hyperspectral imaging and deep learning by Taojing Ran, Wei Huang, Xianzheng Qin, Xingran Xie, Yingjiao Deng, Yundi Pan, Yao Zhang, Ling Zhang, Lili Gao, Minmin Zhang, Dong Wang, Yan Wang, Qingli Li, Chunhua Zhou, Duowu Zou

“…This study developed a method that combines hyperspectral imaging (HSI) technology and a convolutional neural network (CNN) to conduct a cytological diagnosis of PanNETs. …”
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Sistem Rekognisi Citra Digital Bahasa Isyarat Menggunakan Convolutional Neural Network dan Spatial Transformer by Mohammad Alfiano Rizky Mahardika, Novanto Yudistira, Achmad Ridok

“…Data kemudian melalui pemrosesan awal dan diklasifikasikan dengan CNN, lalu didapatkan hasil untuk dianalisis. Apabila hasil memuaskan, model akan diekspor untuk dimasukkan ke dalam aplikasi berbasis web untuk digunakan secara real-time. …”
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Computer Vision with Error Estimation for Reduced Order Modeling of Macroscopic Mechanical Tests by Franck Nguyen, Selim M. Barhli, Daniel Pino Muñoz, David Ryckelynck

“…The CNN recommend a convenient mechanical model available in a dictionary of reduced order models. …”
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Detection of Fungal Infections in Gloriosa Superba Plant Using the Convolution Neural Network Model by Guillermo Napoleón Pelaez-Diaz, Rosa Vílchez-Vásquez, Antonio Huaman-Osorio, R. Mahaveerakannan, S. Pushpa, Nilesh Shelke, Sumitha Jagadibabu, Jenifer Mahilraj

“…We used a deep learning-based convolution neural network (CNN) classifier model to optimize the CNN algorithm parameter for better prediction. …”
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Hybrid Depth-Separable Residual Networks for Hyperspectral Image Classification by Cuijie Zhao, Hongdong Zhao, Guozhen Wang, Hong Chen

“…The HDSRN model organically combines 3D CNN, 2D CNN, multiresidual network ROR, and depth-separable convolutions to extract deeper abstract features. …”
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Patient-Specific Detection of Atrial Fibrillation in Segments of ECG Signals using Deep Neural Networks by Jeyson A. Castillo, Yenny C. Granados, Carlos Augusto Fajardo Ariza

“…This device will be based on a Convolutional Neural Network (CNN). We aim to find a suitable CNN model, which later could be implemented in hardware. …”
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Image Recommendation Algorithm Combined with Deep Neural Network Designed for Social Networks by Shaohui Du, Zhenghan Chen, Haoyan Wu, Yihong Tang, YuanQing Li

“…The experiments show that proposed LSTM model together with CNN feature vectors can outperform other algorithms.…”
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Advancements in the Application of Convolutional Neural Networks in Ultrasound Imaging for Breast Cancer Diagnosis and Treatment by An Zichen, Li Fan

“…Advancing the development of CNN technology in breast US, and improving the generalizability and reproducibility of these models, will significantly promote their translational application in clinical settings.…”
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Fault Diagnosis of Rotating Machinery Based on Convolutional Neural Network and Singular Value Decomposition by Dong Liu, Xu Lai, Zhihuai Xiao, Dong Liu, Xiao Hu, Pei Zhang

“…A novel method of fault diagnosis based on convolutional neural network (CNN), discrete wavelet transform (DWT), and singular value decomposition (SVD) is proposed in this paper. …”
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Machine learning-based prediction of soil organic matter via smartphone by Qingying Gao, Yi Chen, Hui Zhang, Jingjing Chen, Liang Wang

“…The prediction accuracies of RFC, RFLR, CNN and MobileNet were 0.9743, 0.5614, 0.9600 and 0.7915, respectively. …”
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Incisor Malocclusion Using Cut-out Method and Convolutional Neural Network by Muhamad Farhin Harun, Azurah A Samah, Muhammmad Imran Ahmad Shabuli, Hairudin Abdul Majid, Haslina Hashim, Nor Azman Ismail, Syiral Mastura Abdullah, Aspalilah Alias

“…This study has developed a malocclusion classification model using the cut-out method and Convolutional Neural Network (CNN). The cut-out method restructures the input images by standardising the sizes and highlighting the incisor sections of the images which assisted the CNN in accurately classifying the malocclusion. …”
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Comparative Analysis of Deep Learning Techniques for Load Forecasting in Power Systems Using Single-Layer and Hybrid Models by Jiyeon Jang, Beopsoo Kim, Insu Kim

“…The prediction process is performed on the Python platform, and the model that showed the highest accuracy was LSTM-CNN, a hybrid combination of LSTM and CNN models. …”
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Optimizing Pretrained Convolutional Neural Networks for Tomato Leaf Disease Detection by Iftikhar Ahmad, Muhammad Hamid, Suhail Yousaf, Syed Tanveer Shah, Muhammad Ovais Ahmad

“…In this context, our research work focuses on classification and identification of tomato leaf diseases using convolutional neural network (CNN) techniques. We consider four CNN architectures, namely, VGG-16, VGG-19, ResNet, and Inception V3, and use feature extraction and parameter-tuning to identify and classify tomato leaf diseases. …”
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Research on Wood Defects Feature Imbalance Optimization and Recognition by Xiao Wang

“…To this end, two improvements on CNN classifier loss function are proposed to enhance the performance on wood defects recognition. …”
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Lung cancer classification with Convolutional Neural Network Architectures by Shivan H. M. Mohammed, Ahmet Çinar

“…In this work, we implemented pre-trained CNN include: AlexNet, ResNet18, Googlenet, and ResNet50 models. …”
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Bioinformatics-driven deep learning for nail disease diagnosis: A novel approach to improve healthcare outcomes by Ardianto Rian, Yusuf Dede, Sumantri Raden Bagus Bambang, Febrina Dina, Al-Hakim Rosyid R., Ariyanto Arif Setia Sandi

“…The study used a dataset of 655 nail photos that had been pre-processed to 224x224 pixel resolution and categorized into 17categories. The CNN model performed well in identifying illnesses like “Leukonychia,” achieving an overall accuracy of 83%; however, it needs to be improved for underrepresented classifications like “Pale Nail.” …”
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