Results 71 to 80 of about 9,759,453 (201)

All-electron magnetic response with pseudopotentials: NMR chemical shifts

, 2001
A theory for the ab initio calculation of all-electron NMR chemical shifts in insulators using pseudopotentials is presented. It is formulated for both finite and infinitely periodic systems and is based on an extension to the Projector Augmented Wave ...
B.G. Pfrommer, C.G. Van de Walle, C.J. Pickard, Chris J. Pickard, D. Vanderbilt, D.M. Ceperley, D.R. Hamann, F. Buda, F. Mauri, F. Mauri, F. Mauri, F. Mauri, F. Mauri, Francesco Mauri, G. Kresse, G. Valerio, G. Valerio, H. Kageshima, H.J. Monkhorst, H.M. Petrilli, J. Ridard, J.A. Tossell, J.A. Tossell, J.R. Cheeseman, L. Kleinman, M. Kaupp, M.C. Payne, N. Holzwarth, N. Troullier, P. Blaha, P.E. Blöchl, R. Ditchfield, S.H. Vosko, T. Gregor, T.A. Keith, T.A. Keith, W. Kutzelnigg, Y.-G. Yoon   +37 more
core   +2 more sources

Abnormal Load Variation Forecasting in Urban Cities Based on Sample Augmentation and TimesNet

Smart Cities
With the evolving urbanization process in modern cities, the tertiary industry load and residential load start to take up a major proportion of the total urban power load.
Yiyan Li, Zizhuo Gao, Zhenghao Zhou, Yu Zhang, Zelin Guo, Zheng Yan   +5 more
doaj   +1 more source

Few-shot object detection based on positive-sample improvement

Defence Technology, 2023
Traditional object detectors based on deep learning rely on plenty of labeled samples, which are expensive to obtain. Few-shot object detection (FSOD) attempts to solve this problem, learning detection objects from a few labeled samples, but the ...
Yan Ouyang, Xin-qing Wang, Rui-zhe Hu, Hong-hui Xu   +3 more
doaj   +1 more source

Fault State Identification Method with Noise Robustness of Dry Gas Seals Based on Sample-Augmented MA1D-ResNet

Sensors
Dry gas seals are widely used in the petrochemical industry for shaft end sealing of compressors, pumps and other equipment involving flammable, explosive, toxic and harmful media.
Jinlin Chen, Jiahao Li, Xuexing Ding, Wei Xu, Pengju Li, Zhihao Xia   +5 more
doaj   +1 more source

GAN-Based Image Augmentation for Finger-Vein Biometric Recognition

IEEE Access, 2019
Deep learning methods, and especially convolutional neural networks (CNNs), have made a considerable breakthrough in various fields of machine vision, basically by employing large-scale labeled databases.
Jianfeng Zhang, Zhiying Lu, Min Li, Haopeng Wu   +3 more
doaj   +1 more source

Targeting Precision with Data Augmented Samples in Deep Learning [PDF]

, 2019
In the last five years, deep learning (DL) has become the state-of-the-art tool for solving various tasks in medical image analysis. Among the different methods that have been proposed to improve the performance of Convolutional Neural Networks (CNNs), one typical approach is the augmentation of the training data set through various transformations of ...
Pietro Nardelli, Raúl San José Estépar   +1 more
openaire   +2 more sources

Enhanced mixup for improved time series analysis

IJAIN (International Journal of Advances in Intelligent Informatics)
Time series data analysis is crucial for real-world applications. While deep learning has advanced in this field, it still faces challenges, such as limited or poor-quality data.
Khoa Tho Anh Nguyen, Khoa Nguyen, Taehong Kim, Ngoc Hong Tran, Vinh Dinh   +4 more
doaj   +1 more source

Automation of generative adversarial network-based synthetic data-augmentation for maximizing the diagnostic performance with paranasal imaging

Scientific Reports, 2022
Thus far, there have been no reported specific rules for systematically determining the appropriate augmented sample size to optimize model performance when conducting data augmentation.
Hyoun-Joong Kong, Jin Youp Kim, Hye-Min Moon, Hae Chan Park, Jeong-Whun Kim, Ruth Lim, Jonghye Woo, Georges El Fakhri, Dae Woo Kim, Sungwan Kim   +9 more
doaj   +1 more source

Virtual sample generation for model-based prognostics and health management of on-board high-speed train control system

High-Speed Railway, 2023
In view of class imbalance in data-driven modeling for Prognostics and Health Management (PHM), existing classification methods may fail in generating effective fault prediction models for the on-board high-speed train control equipment. A virtual sample
Jiang Liu, Baigen Cai, Jinlan Wang, Jian Wang   +3 more
doaj   +1 more source

Classification of animal sounds in a hyperdiverse rainforest using convolutional neural networks with data augmentation

Ecological Indicators, 2022
To protect tropical forest biodiversity, we need to be able to detect it reliably, cheaply, and at scale. Automated detection of sound producing animals from passively recorded soundscapes via machine-learning approaches is a promising technique towards ...
Yuren Sun, Tatiana Midori Maeda, Claudia Solís-Lemus, Daniel Pimentel-Alarcón, Zuzana Buřivalová   +4 more
doaj   +1 more source