Transfer Learning for CNN-Based Damage Detection in Civil Structures with Insufficient Data by Mona Chamangard, Gholamreza Ghodrati Amiri, Ehsan Darvishan, Zahra Rastin

“…According to the results, the compact CNN can reach 100% accuracy when data are available for training. …”
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Enhanced classification of medicinal plants using deep learning and optimized CNN architectures by Hicham Bouakkaz, Mustapha Bouakkaz, Chaker Abdelaziz Kerrache, Sahraoui Dhelim

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Semantic segmentation of 3D point cloud based on contextual attention CNN by Jun YANG, Jisheng DANG

“…Aiming at the under-segmentation of 3D point cloud semantic segmentation caused by the lack of contextual fine-grained information of the point cloud,an algorithm based on contextual attention CNN was proposed for 3D point cloud semantic segmentation.Firstly,the fine-grained features in local area of the point cloud were mined through the attention coding mechanism.Secondly,the contextual features between multi-scale local areas were captured by the contextual recurrent neural network coding mechanism and compensated with the fine-grained local features.Finally,the multi-head mechanism was used to enhance the generalization ability of the network.Experiments show that the mIoU of the proposed algorithm on the three standard datasets of ShapeNet Parts,S3DIS and vKITTI are 85.4%,56.7% and 38.1% respectively,which has good segmentation performance and good generalization ability.…”
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A CNN-Based Approach for Classical Music Recognition and Style Emotion Classification by Yawen Shi

Subjects: “…CNN…”
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Deep Learning Implementation Using CNN to Classify Bali God Sculpture Pictures by Ni Luh Gede Pivin Suwirmayanti, I Wayan Budi Sentana, I Ketut Gede Darma Putra, Made Sudarma, I Made Sukarsa, Komang Budiarta

“…We compared our CNN model with two other models, AlexNet and ResNet, based on the experimental results. …”
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A Stock Closing Price Prediction Model Based on CNN-BiSLSTM by Haiyao Wang, Jianxuan Wang, Lihui Cao, Yifan Li, Qiuhong Sun, Jingyang Wang

“…This paper proposes a composite model CNN-BiSLSTM to predict the closing price of the stock. …”
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Sign Language Recognition Based on CNN-BiLSTM Using RF Signals by Yajun Zhang, Yuankang Wang, Feng Li, Weiqian Yu, Congcong Wang, Ying Jiang

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An Improved Gesture Segmentation Method for Gesture Recognition Based on CNN and YCbCr by Yan Luo, Gaoxiang Cui, Deguang Li

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Multivariate CNN-LSTM Model for Multiple Parallel Financial Time-Series Prediction by Harya Widiputra, Adele Mailangkay, Elliana Gautama

“…The hybrid ensemble model built in this study is made up of two main components, each with its own set of functions derived from the CNN and LSTM models. For multiple parallel financial time-series estimation, the proposed model is called multivariate CNN-LSTM. …”
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A lightweight power quality disturbance recognition model based on CNN and Transformer by ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian

“…A lightweight power quality disturbances (PQDs) recognition model that integrates convolutional neural network (CNN) and Transformer (CaT) is proposed to address the high number of parameters and computational complexity in existing deep learning-based models. …”
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CNN-Based Channel Estimation Method for OTFS System in Satellite-Ground Scenario by Cheng GUO, Le YU, Lidong ZHU

“…Orthogonal time frequency space (OTFS) is fully applied in high Doppler communication scenarios due to its good Doppler frequency bias and time delay adaptability.The channel estimation methods for OTFS systems have shortcomings such as high complexity and poor BER performance.A CNN-based channel estimation method for OTFS systems in the terrestrial-satellite scenario using a convolutional neural network (CNN) approach was proposed.Simulation results showed that the deep learning-based method outperformed the conventional method in terms of algorithm complexity and BER in the terrestrial-satellite scenario, thus demonstrating that deep learning is a promising tool for channel estimation in OTFS systems.…”
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An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method by Xiaoxun Zhu, Jianhong Zhao, Dongnan Hou, Zhonghe Han

“…This study proposes a symmetrized dot pattern (SDP) characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals. …”
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Remaining Useful Life Prediction of Rolling Bearings Based on CBAM-CNN-LSTM by Bo Sun, Wenting Hu, Hao Wang, Lei Wang, Chengyang Deng

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Impact of Dataset Size on 3D CNN Performance in Intracranial Hemorrhage Classification by Chun-Chao Huang, Hsin-Fan Chiang, Cheng-Chih Hsieh, Bo-Rui Zhu, Wen-Jie Wu, Jin-Siang Shaw

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Recognizing Cow Muzzle Patterns using the Convolution Neural Network (CNN) Algorithm by Sulthon Zamroni, Giri Wahyu Wiriasto, Bulkis Kanata

“…Cattle recognition through their muzzles using the CNN method can produce relatively high results. …”
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Optimized CNN-Based Recognition of District Names of Punjab State in Gurmukhi Script by Sandhya Sharma, Sheifali Gupta, Deepali Gupta, Sapna Juneja, Hamza Turabieh, Lokesh Sharma, Zelalem Kiros Bitsue

“…To recognize the district names, a CNN-based architecture is proposed by employing a Holistic approach. …”
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Few Samples of SAR Automatic Target Recognition Based on Enhanced-Shape CNN by Mengmeng Huang, Fang Liu, Xianfa Meng

“…Wherefore, this study designs the enhanced-shape CNN, which enhances the target shape at the input. …”
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Classification of Riau Batik Motifs Using the Convolutional Neural Network (CNN) Algorithm by Dhea Amanda Ramadhan, Dian Ramadhani

Subjects: “…classification, cnn, deep learning, riau batik.…”
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FAULT DIAGNOSIS METHOD OF DIESEL ENGINE BASED ON PCA-EDT-CNN (MT) by BAI YunJie, JIA XiSheng, LIANG QingHai, MA YunFei, WEN Liang

“…Aiming at the problem that the vibration signal in diesel engine fault diagnosis is non-stationary and nonlinear, and the original signal is directly input into the Convolutional Neural Network（CNN） for fault diagnosis with poor effect, a new method based on PCA-EDT-CNN is proposed. …”
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DC-BiLSTM-CNN Algorithm for Sentiment Analysis of Chinese Product Reviews by Yuanfang Dong, Xiaofei Li, Meiling He, Jun Li

“…This paper introduces an innovative Dual-Channel BiLSTM-CNN (DC-BiLSTM-CNN) algorithm. Based on the language characteristics of Chinese product reviews, a sentiment analysis algorithm, dual channel BiLSTM-CNN (DC-BiLSTM-CNN), is proposed. …”
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