Accelerating Deep Neural Networks implementation: A survey by Meriam Dhouibi, Ahmed Karim Ben Salem, Afef Saidi, Slim Ben Saoud

“…Deploying such Deep Neural Networks (DNN) on embedded devices is still a challenging task considering the massive requirement of computation and storage. …”
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Arrhythmia Classification Techniques Using Deep Neural Network by Ali Haider Khan, Muzammil Hussain, Muhammad Kamran Malik

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Classification of ECG signals using deep neural networks by Nadour Mohamed, Cherroun Lakhmissi, Hadroug Nadji

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A deep neural network for general scattering matrix by Jing Yongxin, Chu Hongchen, Huang Bo, Luo Jie, Wang Wei, Lai Yun

Subjects: “…deep neural network…”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…Abstract The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. …”
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An Enhanced Deep Neural Network for Predicting Workplace Absenteeism by Syed Atif Ali Shah, Irfan Uddin, Furqan Aziz, Shafiq Ahmad, Mahmoud Ahmad Al-Khasawneh, Mohamed Sharaf

“…The efficacy of the proposed method is tested with traditional machine learning techniques, and the results indicate 90.6% performance in Deep Neural Network as compared to 73.3% performance in a single-layer Neural Network and 82% performance in Decision Tree, SVM, and Random Forest. …”
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Severity Classification of Conjunctival Hyperaemia by Deep Neural Network Ensembles by Hiroki Masumoto, Hitoshi Tabuchi, Tsuyoshi Yoneda, Shunsuke Nakakura, Hideharu Ohsugi, Tamaki Sumi, Atsuki Fukushima

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Gradient Amplification: An Efficient Way to Train Deep Neural Networks by Sunitha Basodi, Chunyan Ji, Haiping Zhang, Yi Pan

“…Improving performance of deep learning models and reducing their training times are ongoing challenges in deep neural networks. There are several approaches proposed to address these challenges, one of which is to increase the depth of the neural networks. …”
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Water quality assessment for aquaculture using deep neural network by Rajeshwarrao Arabelli, T. Bernatin, Venkataramana Veeramsetty

Subjects: “…Deep neural networks…”
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Deep Neural Network Model Forecasting for Financial and Economic Market by Fan Chen

“…In view of the Internet financial market dynamic (volume and daily trading), it is proposed based on a deep neural network for fusion level time series prediction model. …”
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SPECTRUMNET: Cooperative Spectrum Monitoring Using Deep Neural Networks by M. Suriya, M. G. Sumithra

“…A hybrid deep learning model called SPECTRUMNET (spectrum sensing using deep neural network) is presented. It can quickly and accurately monitor the spectrum from spectrogram images by utilizing cyclostationary features and convolutional neural networks (CNN). …”
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Tilted-Mode All-Optical Diffractive Deep Neural Networks by Mingzhu Song, Xuhui Zhuang, Lu Rong, Junsheng Wang

Subjects: “…diffractive deep neural networks…”
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Prediction of Future Terrorist Activities Using Deep Neural Networks by M. Irfan Uddin, Nazir Zada, Furqan Aziz, Yousaf Saeed, Asim Zeb, Syed Atif Ali Shah, Mahmoud Ahmad Al-Khasawneh, Marwan Mahmoud

“…Five different models based on deep neural network (DNN) are created to understand the behavior of terrorist activities such as is the attack going to be successful or not? …”
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Yogasana classification using Deep Neural Network: A Unique Approach by Rishi Raj, Rajesh Mukherjee, Bidesh Chakraborty

“…In this research work, we have automatically identified different Yogasanas from images using a deep neural network. For our work we have considered 10 very popular categories of Yogasana and built a dataset of volume 800 images. …”
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Human Activity Recognition Using Graph Structures and Deep Neural Networks by Abed Al Raoof K. Bsoul

“…This research presents a novel HAR system combining graph structures with deep neural networks to capture both spatial and temporal patterns in activities. …”
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Learning From High-Cardinality Categorical Features in Deep Neural Networks by Mustafa Murat Arat

Subjects: “…deep neural networks…”
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DWNet: Dual-Window Deep Neural Network for Time Series Prediction by Jin Fan, Yipan Huang, Ke Zhang, Sen Wang, Jinhua Chen, Baiping Chen

“…In this paper, we propose a dual-window deep neural network (DWNet) to predict time series. The dual-window mechanism allows the model to mine multigranularity dependencies of time series, such as local information obtained from a short sequence and global information obtained from a long sequence. …”
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Analysis of Consumer Behavior Data Based on Deep Neural Network Model by Shijiao Yuan

“…In order to improve the accuracy of sample classification and maximize the output function, genetic algorithm is used to optimize the samples. A deep neural network structure algorithm is proposed to classify customer transaction data samples. …”
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An Intelligent Health Monitoring Model Based on Fuzzy Deep Neural Network by Tianye Xing, Yidan Wang, Yingxue Liu, Qi Wu, Rong Ma, Xiaoling Shang

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Well Control Optimization of Waterflooding Oilfield Based on Deep Neural Network by Lihui Tang, Junjian Li, Wenming Lu, Peiqing Lian, Hao Wang, Hanqiao Jiang, Fulong Wang, Hongge Jia

“…This paper proposes a new method of a well control optimization method based on a multi-input deep neural network. This method takes the production history data of the reservoir as the main input and the saturation field as the auxiliary input and establishes a multi-input deep neural network for learning, forming a production dynamic prediction model instead of conventional numerical simulators. …”
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