Tilted-Mode All-Optical Diffractive Deep Neural Networks by Mingzhu Song, Xuhui Zhuang, Lu Rong, Junsheng Wang

Subjects: “…diffractive deep neural networks…”
Get full text

Classification of Melanoma Cancer Using Deep Convolutional Neural Networks by Emrah Dönmez, Ali Güneş

“…This study investigates the application of machine learning techniques to diagnose skin lesions, focusing on differentiating between benign moles and malignant melanoma. A Convolutional Neural Network (CNN) model was developed to explore machine learning's efficacy in this context. …”
Get full text

Analysis of Artificial Neural Network: Architecture, Types, and Forecasting Applications by Manogaran Madhiarasan, Mohamed Louzazni

“…The artificial neural network reduces humanity and society’s burden to solve complex problems highly efficiently. …”
Get full text

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? …”
Get full text

Neural network-based robot localization using visual features by Felipe Trujillo-Romero

“…The map is modeled using a neural network, where each neuron corresponds to an absolute position in the room. …”
Get full text

Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks by Amaury Vanvinckenroye, Gilles Vandewalle, Christophe Phillips, Sarah L. Chellappa

Get full text

Deep weighted survival neural networks to survival risk prediction by Hui Yu, Qingyong Wang, Xiaobo Zhou, Lichuan Gu, Zihao Zhao

Subjects: Get full text

Application of Neural Networks in Financial Time Series Forecasting Models by Xinhui Li

“…As an algorithm model that can simulate the biological visual system, the convolutional neural network can predict the numerical trend of the next period of time based on known data. …”
Get full text

Review on Deep Learning and Neural Network Implementation for Emotions Recognition by Renas Rajab Asaad

Subjects: Get full text

FPGA-QNN: Quantized Neural Network Hardware Acceleration on FPGAs by Mustafa Tasci, Ayhan Istanbullu, Vedat Tumen, Selahattin Kosunalp

“…Recently, convolutional neural networks (CNNs) have received a massive amount of interest due to their ability to achieve high accuracy in various artificial intelligence tasks. …”
Get full text

Neural Network of Predictive Motor Timing in the Context of Gender Differences by Pavel Filip, Jan Lošák, Tomáš Kašpárek, Jiří Vaníček, Martin Bareš

Get full text

Intelligent Psychology Teaching System Based on Adaptive Neural Network by Xiaojia Pang

“…Firstly, the basic structure of the neural network in the teaching system is introduced, the psychological teaching algorithm based on the adaptive neural network is introduced, the ideas are formulated, and the four learning methods and the design elements of the adaptive neural network are described. …”
Get full text

Transverse-layer partitioning of artificial neural networks for image classification by N.A. Vershkov, M.G. Babenko, N.N. Kuchukov, V.A. Kuchukov, N.N. Kucherov

Subjects: Get full text

Convolutional Neural Networks for Software Defect Categorization: An Empirical Validation by Ruchika Malhotra, Madhukar Cherukuri

“…Leveraging the prevailing advancements in computational power and storage capacity, the study present a novel defect categorization model built upon Convolutional Neural Networks (CNNs). Extensive experiments were carried out on defect datasets from five Android operating system application modules, leading to the creation of 60 SDC models (5 datasets x 4 feature sets x 3 approaches). …”
Get full text

Speech Separation Using Convolutional Neural Network and Attention Mechanism by Chun-Miao Yuan, Xue-Mei Sun, Hu Zhao

“…By analyzing the characteristics of the convolutional neural network and attention mechanism, it can be found that the convolutional neural network can effectively extract low-dimensional features and mine the spatiotemporal structure information in the speech signals, and the attention mechanism can reduce the loss of sequence information. …”
Get full text

Assessment of Artificial Neural Networks for Hourly Solar Radiation Prediction by Tamer Khatib, Azah Mohamed, K. Sopian, M. Mahmoud

“…This paper presents an assessment for the artificial neural network (ANN) based approach for hourly solar radiation prediction. …”
Get full text

Application of Optimized BP Neural Network In Financial Alert System by Qiaoyi Gao

“…Based on this, main body of a book studies and analyzes the request of optimized BP neural network in financial alert system. Based on the financial early warning and a brief analysis of the development requirements of BP neural network, this paper establishes a financial early warning model for BP neural network. …”
Get full text

Estimation of Approximating Rate for Neural Network inLwp Spaces by Jian-Jun Wang, Chan-Yun Yang, Jia Jing

“…The results obtained are helpful in understanding the approximation capability and topology construction of the sigmoidal neural networks.…”
Get full text

Study on Ductility of Ti Aluminide Using Artificial Neural Network by R. K. Gupta, Rama Mehta, Vijaya Agarwala, Bhanu Pant, P. P. Sinha

“…Using the reported data, the present paper aims to optimize the experimental conditions through computational modeling using artificial neural network (ANN). Ductility database were prepared, and three parameters, namely, alloy type, grain size, and heat treatment cycle were selected for modeling. …”
Get full text

Efficient Artificial Neural Network for Smart Grid Stability Prediction by Saeed Mohsen, Mohit Bajaj, Hossam Kotb, Mukesh Pushkarna, Sadam Alphonse, Sherif S. M. Ghoneim

“…From this perspective, this process is too much time consuming, thus it should predict a smart grid stability via artificial intelligence (e.g., neural networks). Recent advances in the accuracy of neural network have effective solutions to solving the smart grid stability prediction issues, but it remains necessary to develop high performance neural networks that give higher accuracy. …”
Get full text