Calponin 3 Regulates Myoblast Proliferation and Differentiation Through Actin Cytoskeleton Remodeling and YAP1-Mediated Signaling in Myoblasts by Mai Thi Nguyen, Quoc Kiet Ly, Thanh Huu Phan Ngo, Wan Lee

“…An actin-binding protein, known as Calponin 3 (CNN3), modulates the remodeling of the actin cytoskeleton, a fundamental process for the maintenance of skeletal muscle homeostasis. …”
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A real time monitoring system for accurate plant leaves disease detection using deep learning by Kazi Naimur Rahman, Sajal Chandra Banik, Raihan Islam, Arafath Al Fahim

“…The highest accuracy rates for disease detection were: 100 ​% for potato (custom CNN), 98 ​% for tomato (InceptionV3, custom CNN, VGG16), 100 ​% for pepper bell (MobileNet, custom CNN), 100 ​% for apple (MobileNet, Xception), 98 ​% for corn (custom CNN), 99 ​% for grape (custom CNN, VGG19, DenseNet121), 100 ​% for peach (VGG16, custom CNN), and 98 ​% for rice (DenseNet121). …”
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Pengaruh Dataset terhadap Performa Convolutional Neural Network pada Klasifikasi X-Ray Pasien Covid-19 by Chyntia Raras Ajeng Widiawati

“…Untuk itu perlu analisa pengaruh dataset terhadap performa model CNN yang digunakan. Penelitian ini bertujuan untuk melihat pengaruh kualitas dataset dan jumlah dataset terhadap performa CNN pada klasifikasi X-Ray pasien COVID-19. …”
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Antiangiogenic therapy with recombinant human endostatin may improve blood perfusion of cervical node with necrosis in nasopharyngeal carcinoma patients: a preliminary study by usi... by Zhendong Yang, Huimin Xiao, Xigui Li, Zhuxin Wei, Min Kang, Rensheng Wang, Jianyuan Huang

“…BackgroundThe cervical node with necrosis (CNN) is an important poor prognostic factor for nasopharyngeal carcinoma (NPC) patients. …”
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Vehicle Attribute Recognition for Normal Targets and Small Targets Based on Multitask Cascaded Network by Fang Liu, Yong Zhang, Hua Gong, Ke Xu, Ligang Cai

“…For vehicle targets with normal size, the multitask cascaded convolution neural network MC-CNN-NT uses the improved Faster R-CNN as the location subnetwork. …”
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Multimodal Deep Feature Fusion (MMDFF) for RGB-D Tracking by Ming-xin Jiang, Chao Deng, Ming-min Zhang, Jing-song Shan, Haiyan Zhang

“…MMDFF model consists of four deep Convolutional Neural Networks (CNNs): Motion-specific CNN, RGB- specific CNN, Depth-specific CNN, and RGB-Depth correlated CNN. …”
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Intelligent Fault Diagnosis of Aeroengine Sensors Using Improved Pattern Gradient Spectrum Entropy by Huihui Li, Linfeng Gou, Hua Zheng, Huacong Li

“…A new intelligent fault diagnosis scheme combining improved pattern gradient spectrum entropy (IPGSE) and convolutional neural network (CNN) is proposed in this paper, aiming at the problem of poor fault diagnosis effect and real-time performance when CNN directly processes one-dimensional time series signals of aeroengine. …”
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Deteksi Covid-19 pada Citra Sinar-X Dada Menggunakan Deep Learning yang Efisien by Novanto Yudistira, Agus Wahyu Widodo, Bayu Rahayudi

“…Selain itu, CNN dengan parameter yang lebih kecil juga dapat untuk diaplikasikan pada FPGA dan perangkat keras lainnya yang mempunyai kapasitas memori terbatas. …”
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Predictive Control for Steel Rib Bending Based on Deep Learning by Yijiang Xia, Jinhui Luo, Zhuolin Ou, Xin Han, Junlin Deng, Ning Wu

“…This study proposes control methods for cold bending machines based on deep learning models to address this challenge, including CNN and Transformer-CNN (T-CNN), to predict the elastic spring-back rate of cold-processed metal profiles and generate precise control pulses for achieving target bending angles. …”
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Ensemble of feature augmented convolutional neural network and deep autoencoder for efficient detection of network attacks by Selvakumar B, Sivaanandh M, Muneeswaran K, Lakshmanan B

“…In FA-CNN, CNN is trained with augmented features selected using Mutual Information. …”
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Automatic Detection of Small Intestinal Hookworms in Capsule Endoscopy Images Based on a Convolutional Neural Network by Tao Gan, Yulin Yang, Shuaicheng Liu, Bing Zeng, Jinlin Yang, Kai Deng, Junchao Wu, Li Yang

“…We sought to develop an artificial intelligence system with a convolutional neural network (CNN) to automatically detect hookworms in CE images. …”
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More Efficient and Reliable: Identifying RRab Stars with Blazhko Effect by Deep Convolutional Neural Network by Nan Jiang, Tianrui Sun, Siyuan Pan, Lingzhi Wang, Xue Li, Bin Sheng, Xiaofeng Wang

“…Similarly, the light-curve parameters of these classified BL/non-BL candidates by our CNN method from the GB region resemble those observed in the literature, confirming the reliability of our CNN classifications. …”
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Semantic-Based Classification of Long Texts on Higher Education in China by Chun Li, Yanying Fei

“…To solve these problems, this paper improves the convolutional neural network (CNN) into the HE-CNN classification model for HE texts. …”
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Deep Learning-Based Damage Assessment in Cherry Leaves by Burakhan Cubukcu, Hazel BOZCU

“…Additionally, hybrid models (CNN+RNN) were found to achieve higher performance than the classical CNN model. …”
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Intensive Cold-Air Invasion Detection and Classification with Deep Learning in Complicated Meteorological Systems by Ming Yang, Hao Ma, Bomin Chen, Guangtao Dong

“…Finally, the improved faster R-CNN model is used to identify, classify, and locate the path of NITR events. …”
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Diagnosis of oral cancer using deep learning algorithms by Mayra Alejandra Dávila Olivos, Henry Miguel Herrera Del Águila, Félix Melchor Santos López

“…A deep convolutional neural network (CNN) model, augmented with data, was proposed to enhance oral cancer diagnosis. …”
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Transformer Inrush Current and Internal Fault Discrimination Using Multitypes of Convolutional Neural Network Techniques by Abedalgany Abedallah Athamneh, Ali Mohammad Alqudah

“…This research succeeded in proposing two robust and efficient CNN models; the first one is the 1D CNN, which takes the sole signal without any transformation, while the second model is the 2D CNN, which takes the short-time Fourier transform of the signal. …”
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Classification of Teleseismic Shear Wave Splitting Measurements: A Convolutional Neural Network Approach by Yanwei Zhang, Stephen S. Gao

“…Application of the trained CNN to broadband seismic data recorded in south central Alaska reveals that CNN classifies 97.0% of human selected measurements as acceptable, and revealed ∼30% additional measurements. …”
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Bearing Fault Diagnosis of End-to-End Model Design Based on 1DCNN-GRU Network by Liu Zhiwei

“…A convolutional neural network (CNN) is good at mining spatial features of samples and has the advantage of “end-to-end.” …”
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Highway Travel Time Prediction of Segments Based on ANPR Data considering Traffic Diversion by Wenjun Du, Bo Sun, Jiating Kuai, Jiemin Xie, Jie Yu, Tuo Sun

“…The experimental results indicate that LSTM-CNN learns spatial, temporal, and depth information better than the state-of-the-art traffic forecasting models, so LSTM-CNN can predict more accurate travel time. …”
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