Evaluation of Prediction Performances of Deep Learning Models for the Aerodynamic Characteristics of Flettner Rotors by Seo Janghoon, Park Jung Yoon, Ma Juhwan, Kim Young Bu, Park Dong-Woo

Subjects: “…deep learning model…”
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A Deep Learning-Based Approach to Enable Action Recognition for Construction Equipment by Jinyue Zhang, Lijun Zi, Yuexian Hou, Mingen Wang, Wenting Jiang, Da Deng

“…The contributions of this research are as follows: (1) the development of a comprehensive video dataset of 2,064 clips with five action types for excavators and dump trucks; (2) a new deep learning-based CEAR approach (known as a simplified temporal convolutional network or STCN) that combines a convolutional neural network (CNN) with long short-term memory (LSTM, an artificial recurrent neural network), where CNN is used to extract image features and LSTM is used to extract temporal features from video frame sequences; and (3) the comparison between this proposed new approach and a similar CEAR method and two of the best-performing HAR approaches, namely, three-dimensional (3D) convolutional networks (ConvNets) and two-stream ConvNets, to evaluate the performance of STCN and investigate the possibility of directly transferring HAR approaches to the field of CEAR.…”
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Dimensionality cutback and deep learning algorithms efficacy as to the breast cancer diagnostic dataset by Gennady Chuiko, Denys Honcharov

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Deep learning-based object detection algorithms in medical imaging: Systematic review by Carina Albuquerque, Roberto Henriques, Mauro Castelli

Subjects: “…Deep learning…”
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Deep Learning-Based Crack Monitoring for Ultra-High Performance Concrete (UHPC) by Dongling Wu, Hongxiang Zhang, Yiying Yang

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Development of an autonomous chess robot system using computer vision and deep learning by Truong Duc Phuc, Bui Cao Son

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Artificial intelligence in suicide prevention: Utilizing deep learning approach for early detection by Vikas Gaur, Gaurav Maggu, Khushboo Bairwa, Suprakash Chaudhury, Sana Dhamija, Tahoora Ali

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Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation by Xianzhi Deng, Xiaolong Hu, Liangsheng Shi, Chenye Su, Jinmin Li, Shuai Du, Shenji Li

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A survey of MRI-based brain tissue segmentation using deep learning by Liang Wu, Shirui Wang, Jun Liu, Lixia Hou, Na Li, Fei Su, Xi Yang, Weizhao Lu, Jianfeng Qiu, Ming Zhang, Li Song

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Deep learning based physical layer wireless communication techniques:opportunities and challenges by Guan GUI, Yu WANG, Hao HUANG

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Method of Evaluating and Predicting Traffic State of Highway Network Based on Deep Learning by Jiayu Liu, Xingju Wang, Yanting Li, Xuejian Kang, Lu Gao

“…The accurate evaluation and prediction of highway network traffic state can provide effective information for travelers and traffic managers. Based on the deep learning theory, this paper proposes an evaluation and prediction model of highway network traffic state, which consists of a Fuzzy C-means (FCM) algorithm-based traffic state partition model, a Long Short-Term Memory (LSTM) algorithm-based traffic state prediction model, and a K-Means algorithm-based traffic state discriminant model. …”
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Analysis of Psychological and Emotional Tendency Based on Brain Functional Imaging and Deep Learning by Lin Zhou

“…Therefore, a personal emotional tendency analysis method based on brain functional imaging and deep learning is proposed. Firstly, the EEG forward model is established according to functional magnetic resonance imaging (fMRI), and the transfer matrix from the signal source at the cerebral cortex to the head surface electrode is obtained. …”
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Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method by Yuhan Jia, Jianping Wu, Ming Xu

“…Experimental results indicate that, with the consideration of additional rainfall factor, the deep learning predictors have better accuracy than existing predictors and also yield improvements over the original deep learning models without rainfall input. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…This study proposes a novel optimisation approach utilising deep learning to tackle these challenges. The integration of Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO) offers a practical approach to addressing the dynamic characteristics of IoT applications. …”
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On the assessment and reliability of political and ideological education in colleges using deep learning methods by Yongsheng Ma, Xianhui Sun, Aiqun Ma

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A survey on deep learning for polyp segmentation: techniques, challenges and future trends by Jiaxin Mei, Tao Zhou, Kaiwen Huang, Yizhe Zhang, Yi Zhou, Ye Wu, Huazhu Fu

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Validation of deep-learning accelerated quantitative susceptibility mapping for deep brain nuclei by Ying Zhou, Ying Zhou, Lingyun Liu, Shan Xu, Yongquan Ye, Ruiting Zhang, Minming Zhang, Jianzhong Sun, Peiyu Huang

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Deep Learning- and Word Embedding-Based Heterogeneous Classifier Ensembles for Text Classification by Zeynep H. Kilimci, Selim Akyokus

“…The use of ensemble learning, deep learning, and effective document representation methods is currently some of the most common trends to improve the overall accuracy of a text classification/categorization system. …”
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Indicator Selection for Topic Popularity Definition Based on AHP and Deep Learning Models by Yuling Hong, Qishan Zhang

“…Moreover, its future popularity can be predicted by deep learning methods. At the same time, a new application field of deep learning technology has been further discovered and verified. …”
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Leveraging paired mammogram views with deep learning for comprehensive breast cancer detection by Jae Won Seo, Young Jae Kim, Kwang Gi Kim

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