Towards Pedestrian Target Detection with Optimized Mask R-CNN by Dong-Hao Chen, Yu-Dong Cao, Jia Yan

“…Aiming at the problem of low pedestrian target detection accuracy, we propose a detection algorithm based on optimized Mask R-CNN which uses the latest research results of deep learning to improve the accuracy and speed of detection results. …”
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Efficient recognition of Parkinson’s disease mice on stepping characters with CNN by Yunsong Luo, Yiqi Huang, Guangzhan Fang, Ningping Tan, Yezhong Tang

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CNN Based Automatic Speech Recognition: A Comparative Study by Hilal Ilgaz, Beyza Akkoyun, Özlem Alpay, M. Ali Akcayol

“…The most advanced results have been obtained with speech recognition systems created using convolutional neural network (CNN) and recurrent neural networks (RNN). Since CNNs can capture local features effectively, they are applied to tasks with relatively short-term dependencies, such as keyword detection or phoneme- level sequence recognition. …”
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A CNN-LSTM-Based Model to Forecast Stock Prices by Wenjie Lu, Jiazheng Li, Yifan Li, Aijun Sun, Jingyang Wang

“…At the same time, based on machine learning long short-term memory (LSTM) which has the advantages of analyzing relationships among time series data through its memory function, we propose a forecasting method of stock price based on CNN-LSTM. In the meanwhile, we use MLP, CNN, RNN, LSTM, CNN-RNN, and other forecasting models to predict the stock price one by one. …”
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Robust CNN for facial emotion recognition and real-time GUI by Imad Ali, Faisal Ghaffar

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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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Oriented R-CNN With Disentangled Representations for Product Packaging Detection by Jiangyi Pan, Jianjun Yang, Yinhao Liu, Yijie Lv

“…Based on these insights, we propose a pioneering object detection method tailored for industrial environments, termed as oriented R-CNN with disentangled representations (ORDR). The experimental results indicate that our proposed method outperforms better than some of the state-of-the-art detection techniques available.…”
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CNN-based continuous authentication scheme for vehicular digital twin by Chengzhe LAI, Xinwei ZHANG, Guanjie LI, Dong ZHENG

“…To address vehicle identity legitimacy verification issues, a continuous authentication scheme for vehicular digital twin based on convolutional neural network (CNN) was proposed.Specifically, the digital twin was used to acquire the data collected by the vehicle sensors for training the CNN deployed on the digital twin.Then, principal component analysis was performed to select appropriate typical features for the classifier.Using the features extracted by the CNN, the one-class support vector machine (OC-SVM) classifier was trained in the registration phase and the data was classified in the authentication phase, which consequently verified the current vehicle as a legitimate or malicious vehicle.Simulation results show that the proposed scheme has outstanding advantages and outperforms the existing schemes in terms of performance and accuracy.…”
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Brain Tumor Detection Using a Deep CNN Model by Sonia Ben Brahim, Samia Dardouri, Ridha Bouallegue

“…The proposed model is built upon the state-of-the-art CNN architecture VGG16, employing a data augmentation approach. …”
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A Time-Aware CNN-Based Personalized Recommender System by Dan Yang, Jing Zhang, Sifeng Wang, XueDong Zhang

“…In this paper, a time-aware convolutional neural network- (CNN-) based personalized recommender system TC-PR is proposed. …”
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R-CNN-Based Satellite Components Detection in Optical Images by Yulang Chen, Jingmin Gao, Kebei Zhang

“…First, on the basis of the Mask R-CNN, we combine the DenseNet, ResNet, and FPN to construct a new feature extraction structure and obtain the R-CNN based satellite-component-detection model (RSD). …”
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ROLLING BEARING FAULT DIAGNOSIS BASED ON VMD-CWT-CNN by CHEN DaiJun, CHEN LiLi, DONG ShaoJiang

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Breast cancer classification based on hybrid CNN with LSTM model by Mourad Kaddes, Yasser M. Ayid, Ahmed M. Elshewey, Yasser Fouad

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Intelligent Diagnosis Method of Gear Faults based on MGAN and CNN by Zheng Li, Shengli Wu, Wenting Xing, Shiyong Liao

“…An intelligent diagnosis method of gear faults based on MGAN （Mixture Generative Adversarial Nets） and CNN （Convolutional Neural Networks） is proposed. …”
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CNN-Based Time Series Decomposition Model for Video Prediction by Jinyoung Lee, Gyeyoung Kim

“…This study introduces a CNN-based time series decomposition model for video prediction. …”
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An Automatic System for Atrial Fibrillation by Using a CNN-LSTM Model by Fengying Ma, Jingyao Zhang, Wei Chen, Wei Liang, Wenjia Yang

“…The CNN-LSTM is feeded by processed data to automatically detect AF signals. …”
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Enhancing Sentiment Analysis with a CNN-Stacked LSTM Hybrid Model by Shao Shuaijie

“…This model uses CNN for its advantage of capturing local features in the sequence after the embedding process, and LSTM for its advantage of capturing long-term dependencies in such sequential data after CNN layer. …”
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Deep Image Synthesis, Analysis and Indexing Using Integrated CNN Architectures by Muhammad Arslan, Muhammad Asad, Ali Haider Khan, Sajid Iqbal, Muhammad Nabeel Asghar, Abdullah Abdulrhman Alaulamie

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A Block-Based and Highly Parallel CNN Accelerator for Seed Sorting by Xiaoting Sang, Zhenghui Hu, Huanyu Li, Chunlei Li, Zhoufeng Liu

“…The seed sorting methods based on convolutional neural networks (CNNs) have achieved excellent recognition accuracy on large-scale pretrained network models. However, CNN inference is a computationally intensive process that often requires hardware acceleration to operate in real time. …”
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Robustness design of templates for logic OR operation CNN in gray-scale images by Qun ZHANG, Le-quan MIN

Subjects: “…CNN…”
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