Výsledky vyhledávání - "Probability and Statistics in Computer Science"

Gazelle optimization algorithm: a novel nature-inspired metaheuristic optimizer Autor Agushaka, Jeffrey O., Ezugwu, Absalom E., Abualigah, Laith

“…This study proposes a novel population-based metaheuristic algorithm called the Gazelle Optimization Algorithm (GOA), inspired by the gazelles’ survival…”
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A deep learning approach for Parkinson’s disease diagnosis from EEG signals Autor Oh, Shu Lih, Hagiwara, Yuki, Raghavendra, U., Yuvaraj, Rajamanickam, Arunkumar, N., Murugappan, M., Acharya, U. Rajendra

“… In this work, we have used the EEG signals of twenty PD and twenty normal subjects in this study…”
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Optimizing epileptic seizure recognition performance with feature scaling and dropout layers Autor Omar, Ahmed, Abd El-Hafeez, Tarek

“… The study employed a dataset of Electroencephalography (EEG) recordings from multiple subjects and trained nine deep learning architectures with different preprocessing techniques…”
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A review on COVID-19 forecasting models Autor Rahimi, Iman, Chen, Fang, Gandomi, Amir H.

“…, which were performed on COVID-19 data from the Scopus and Web of Science databases. For the above-mentioned analysis, keywords and subject areas are addressed…”
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A novel explainable machine learning approach for EEG-based brain-computer interface systems Autor Ieracitano, Cosimo, Mammone, Nadia, Hussain, Amir, Morabito, Francesco Carlo

“…Electroencephalographic (EEG) recordings can be of great help in decoding the open/close hand’s motion preparation. To this end, cortical EEG source signals in…”
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Breast cancer diagnosis using GA feature selection and Rotation Forest Autor Aličković, Emina, Subasi, Abdulhamit

“…Breast cancer is one of the primary causes of death among the women worldwide, and the accurate diagnosis is one of the most significant steps in breast cancer…”
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Double debiased estimation and inference for longitudinal generalized linear models with hidden confounders: Double debiased estimation and inference Autor Fei, Yuxin, Liu, Jin, Wang, Lei

“…The hidden confounding model has been widely applied in many fields. Without adjusting for the hidden confounders, the estimators from the standard methods of…”
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A deep multi-source adaptation transfer network for cross-subject electroencephalogram emotion recognition Autor Wang, Fei, Zhang, Weiwei, Xu, Zongfeng, Ping, Jingyu, Chu, Hao

“…In real-world application of affective brain–computer interface (aBCI), individual differences across subjects and non-stationary characteristics of electroencephalogram (EEG…”
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Two-stage deep learning model for Alzheimer’s disease detection and prediction of the mild cognitive impairment time Autor El-Sappagh, Shaker, Saleh, Hager, Ali, Farman, Amer, Eslam, Abuhmed, Tamer

“…Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by thinking, behavioral and memory impairments. Early prediction of…”
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A systematic review and meta-analysis of artificial neural network application in geotechnical engineering: theory and applications Autor Moayedi, Hossein, Mosallanezhad, Mansour, Rashid, Ahmad Safuan A., Jusoh, Wan Amizah Wan, Muazu, Mohammed Abdullahi

“…Artificial neural network (ANN) aimed to simulate the behavior of the nervous system as well as the human brain. Neural network models are mathematical…”
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Classification of olive leaf diseases using deep convolutional neural networks Autor Uğuz, Sinan, Uysal, Nese

“…In recent years, there have been significant achievements in object classification with various techniques using several deep learning architectures. These…”
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Enhancing real-time fire detection: an effective multi-attention network and a fire benchmark Autor Khan, Taimoor, Khan, Zulfiqar Ahmad, Choi, Chang

“…Over the past decades, fire has been considered one of the most serious natural disasters because of its devastating nature, rapid spread, and high impact on…”
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Linear quantile mixed models Autor Geraci, Marco, Bottai, Matteo

“… In a previous publication (Geraci and Bottai in Biostatistics 8:140–154, 2007 ), we proposed a conditional quantile regression model for continuous responses where subject…”
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Monte Carlo statistical methods Autor Robert, Christian P., Casella, George

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De-noising boosting methods for variable selection and estimation subject to error-prone variables Autor Chen, Li-Pang

“…Boosting is one of the most powerful statistical learning methods that combines multiple weak learners into a strong learner. The main idea of boosting is to…”
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Heterogeneous Analysis of Longitudinal Profiles using Adaptive Banded Precision Matrices via Penalized Fusion: Heterogeneous Analysis of Longitudinal Profiles using Adaptive Autor Liang, Chunhui, Ma, Wenqing

“… In this paper, we assume that subjects are sampled from a Gaussian mixture distribution, and incorporate regularized bandable precision matrix structure information for each subgroup…”
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A review on evaluating mental stress by deep learning using EEG signals Autor Badr, Yara, Tariq, Usman, Al-Shargie, Fares, Babiloni, Fabio, Al Mughairbi, Fadwa, Al-Nashash, Hasan

“…Mental stress is a common problem that affects individuals all over the world. Stress reduces human functionality during routine work and may lead to severe…”
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Multimodal heterogeneous graph attention network Autor Jia, Xiangen, Jiang, Min, Dong, Yihong, Zhu, Feng, Lin, Haocai, Xin, Yu, Chen, Huahui

“…The real world involves many graphs and networks that are essentially heterogeneous, in which various types of relations connect multiple types of vertices…”
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Unbalanced Longitudinal Data Clustering with a Copula Kernel Mixture Model: Unbalanced Longitudinal Data Clustering Autor Zhang, Xi, Murphy, Orla A., McNicholas, Paul D.

“…Unbalanced longitudinal data appears commonly in practice, for example in cases where measurements are collected at different time points for different subjects and can therefore be sparse and/or irregularly sampled…”
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Automated ECG multi-class classification system based on combining deep learning features with HRV and ECG measures Autor Eltrass, Ahmed S., Tayel, Mazhar B., Ammar, Abeer I.

“…Electrocardiogram (ECG) serves as the gold standard for noninvasive diagnosis of several types of heart disorders. In this study, a novel hybrid approach of…”
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