An Integrated Bearing Fault Diagnosis Method Based on Multibranch SKNet and Enhanced Inception-ResNet-v2 by Baoquan Hu, Jun Liu, Yue Xu, Tianlong Huo

“…Finally, the time-frequency maps of the raw vibration signals are obtained through short-time Fourier transform (STFT) and then sent to the proposed SIR-CNN network for experiments. The experimental results show that the proposed SIR-CNN achieves superior performance compared to other methods.…”
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Hyperspectral Image-Based Identification of Maritime Objects Using Convolutional Neural Networks and Classifier Models by Dongmin Seo, Daekyeom Lee, Sekil Park, Sangwoo Oh

“…The processed data were then analyzed using classifier and convolutional neural network (CNN) models. The results obtained in this study show that CNN models achieved an average test accuracy of 90%, outperforming classifier models, which achieved 83%. …”
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Optimized sequential model for superior classification of plant disease by Yogesh Chimate, Sangram Patil, K. Prathapan, Jaydeep Patil, Jayendra Khot

“…To recover from this and, address these challenges, this study explores deep learning, specifically Convolutional Neural Networks (CNN), as a means to enhance the accuracy and efficiency of plant disease detection. …”
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Discrimination of Fresh Tobacco Leaves with Different Maturity Levels by Near-Infrared (NIR) Spectroscopy and Deep Learning by Yi Chen, Jun Bin, Congming Zou, Mengjiao Ding

“…Moreover, the CNN models with strong feature extraction and learning ability were superior to the KNN, BPNN, SVM, and ELM models. …”
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Deteksi Tingkat Kematangan Buah Pepaya menggunakan Model Convolutional Neural Network by Naufal Putra Sutrisna, Rafifa Addin Sahirah, Khansa Salsabila Sangdiva Laksono, Raditya Atmaja Satria Permadhi, Nadhira Nurannisa, Saqina Salsabila Larasati, Wahayu Widyaning Asmani, Novanto Yudistira

“…Dataset kemudian dilatih menggunakan model CNN untuk mengklasifikasikan buah pepaya berdasarkan warna kulit dan fitur visual lainnya. …”
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Learning a Quantum Computer's Capability by Daniel Hothem, Kevin Young, Tommie Catanach, Timothy Proctor

“…In this work, we propose a hardware-agnostic method to efficiently construct scalable predictive models of a quantum computer's capability for almost any class of circuits and demonstrate our method using convolutional neural networks (CNNs). Our CNN-based approach works by efficiently representing a circuit as a 3-D tensor and then using a CNN to predict its success rate. …”
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Stability Analysis of Impulsive Stochastic Reaction-Diffusion Cellular Neural Network with Distributed Delay via Fixed Point Theory by Ruofeng Rao, Shouming Zhong

“…This paper investigates the stochastically exponential stability of reaction-diffusion impulsive stochastic cellular neural networks (CNN). The reaction-diffusion pulse stochastic system model characterizes the complexity of practical engineering and brings about mathematical difficulties, too. …”
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Residual Neural Network for Direction-of-Arrival Estimation of Multiple Targets in Low SNR by Yanhua Qin

“…Simulation results show that ResNet can achieve significant performance in DOA estimation compared to multiple signal classification, estimation of signal parameters via rotation invariance techniques, convolutional neural network (CNN), and deep complex-valued CNN in low signal-to-noise ratio.…”
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Accelerating Multilingual Cryptocurrency Forensics: An NLP-Driven Approach for Efficient Mnemonic Identification by Hsin-Hsiung Kao

“…We trained and compared four NLP deep learning models: RNN, LSTM, BiLSTM, and TextCNN, on a large-scale, real-world dataset. Our analysis reveals that the Text Convolutional Neural Network (TextCNN) model exhibits superior performance, achieving a 99.9993% accuracy rate, nearly matching the 100% accuracy of the Mnemonic Library Matching Method. …”
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Robust Data-Driven Fault Detection: An Application to Aircraft Air Data Sensors by Yunmei Zhao, Hang Zhao, Jianliang Ai, Yiqun Dong

“…Convolutional neural networks (CNN) and long-short time memory (LSTM) blocks are used in the DNN scheme for accurate FD performances. …”
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Deeply Learned Classifiers for Age and Gender Predictions of Unfiltered Faces by Olatunbosun Agbo-Ajala, Serestina Viriri

“…The two-level CNN architecture includes feature extraction and classification itself. …”
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Enhancing breast cancer prediction through stacking ensemble and deep learning integration by Fatih Gurcan

“…Among these models, CNN stood out for its high accuracy and rapid training time, making it an ideal choice for real-time diagnostic applications. …”
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Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation by Quentin Malé, Corentin J. Lapeyre, Nicolas Noiray

“…Finally, the performances of the CNN model are assessed on test solutions never seen during training. …”
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Securing Urban Landscape: Cybersecurity Mechanisms for Resilient Smart Cities by Qiang Lyu, Sujuan Liu, Zhouyuan Shang

“…The study demonstrates that the CNN-GA framework significantly outperforms traditional cybersecurity methods. …”
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Defect Diagnosis of Gear-Shaft Bearing System Based on the OWF-TSCNN Composed of Wavelet Time-Frequency Map and FFT Spectrum 1 by Peng Dai, JianPing Wang, Lulu Wu, ShuPing Yan, FengTao Wang, Linkai Niu

“…A learning model based on two-stream CNN composed of 1D-CNN and 2D-CNN is established, and the obtained wavelet time-frequency map and FFT spectrum are used as the input. …”
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FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction by Xuekai Zhu, Juan Liu, Jian Zhang, Zhihui Yang, Feng Yang, Xiaolei Zhang

“…Artificial intelligence methods, such as Convolutional Neural Network (CNN), are widely used to facilitate new drug discovery. …”
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Improving timing resolution of BGO for TOF-PET: a comparative analysis with and without deep learning by Francis Loignon-Houle, Nicolaus Kratochwil, Maxime Toussaint, Carsten Lowis, Gerard Ariño-Estrada, Antonio J. Gonzalez, Etiennette Auffray, Roger Lecomte

“…It remains to be explored how timing estimation methods utilizing one (LED), two (TWC), or multiple (CNN) waveform data points compare in CTR performance of BGO scintillators. …”
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Klasifikasi Sinyal Phonocardiogram Menggunakan Short Time Fourier Transform dan Convolutional Neural Network by Muhammad Alwi Adnan Amal, Dodi Zulherman, Rahmat Widadi

“…This study proves that the use of a hamming window in the feature extraction section and 4 convolution layers in the classification section is the best form of the PCG classification system based on STFT and CNN. …”
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Adversarial measurements for convolutional neural network-based energy theft detection model in smart grid by Santosh Nirmal, Pramod Patil, Sagar Shinde

“…Finally, the performance of CNN-Adaboost and other state-of-the-art methods is tested and compared using 10 % and 20 % adversarial data. …”
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Simplified-Boost Reinforced Model-Based Complex Wind Signal Forecasting by Qiushuang Lin, Chunxiang Li

“…The preliminary forecast results by adaptive residual CNN are integrated with historical observed signals as the new input to reconstruct a new forecasting mapping. …”
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