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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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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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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Enhancing breast cancer prediction through stacking ensemble and deep learning integration by Fatih Gurcan

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Multiple sclerosis diagnosis with brain MRI retrieval: A deep learning approach by R.M. Haggag, Eman M. Ali, M.E. Khalifa, Mohamed Taha

“…Experiments on four public MS-MRI datasets demonstrated the end-to-end deep learning framework’s generalizability without extensive pre-processing, with mAP scores of 86.20%, 93.77%, 94.18%, and 90.46%, respectively demonstrating its effectiveness in retrieval. …”
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Pedestrian Motion Path Detection Method Based on Deep Learning and Foreground Detection by Meiman Li, Wenfu Xie

“…For the surveillance video images captured by monocular camera, this paper proposes a method combining foreground detection and deep learning to detect moving pedestrians, making full use of the invariable background of video image. …”
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Emotion Recognition from EEG Signals Using Advanced Transformations and Deep Learning by Jonathan Axel Cruz-Vazquez, Jesús Yaljá Montiel-Pérez, Rodolfo Romero-Herrera, Elsa Rubio-Espino

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Deep-Learning-Based Land Cover Mapping in Franciacorta Wine Growing Area by Girma Tariku, Isabella Ghiglieno, Andres Sanchez Morchio, Luca Facciano, Celine Birolleau, Anna Simonetto, Ivan Serina, Gianni Gilioli

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TriangularSORT: A Deep Learning Approach for Ship Wake Detection and Tracking by Chengcheng Yu, Yanmei Zhang

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An Improvement of the Camshift Human Tracking Algorithm Based on Deep Learning and the Kalman Filter by Van-Truong Nguyen, Duc-Tuan Chu, Dinh-Hieu Phan, Ngoc-Tien Tran

“…In this paper, an improvement of the Camshift human tracking algorithm based on deep learning and the Kalman filter is proposed. To detail an approach by using YOLOv4-tiny to detect a human in real time, Camshift is used to track a particular person and the Kalman filter is applied to enhance the performance of this algorithm in case of occlusion, noise, and different light conditions. …”
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An Optimized Deep-Learning-Based Network with an Attention Module for Efficient Fire Detection by Muhammad Altaf, Muhammad Yasir, Naqqash Dilshad, Wooseong Kim

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Robust Classification of Smartphone Captured Handwritten Document Images Using Deep Learning by K. S. Koushik, B. J. Bipin Nair, N. Shobha Rani, Mohammed Javed

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Emotion Estimation Using Noncontact Environmental Sensing with Machine and Deep Learning Models by Tsumugi Isogami, Nobuyoshi Komuro

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