Results 111 to 120 of about 5,507 (168)

Winter Road Surface Condition Recognition in Snowy Regions Based on Image-to-Image Translation. [PDF]

Sensors (Basel)
Shigesawa A, Yagi M, Takahashi S, Yoshii T, Ishii K, Hu X, Takedomi S, Mori T.   +7 more
europepmc   +1 more source

Neural Network-Based Study for Rice Leaf Disease Recognition and Classification: A Comparative Analysis Between Feature-Based Model and Direct Imaging Model. [PDF]

Food Sci Nutr
Prity FS, Raquib M, Murad SA, Rafi MJ, Bhuiyan MK, Bairagi AK.   +5 more
europepmc   +1 more source

Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection. [PDF]

PLoS One
Zada I, Omran E, Jan S, Alfraihi H, Alsalamah S, Alshahrani A, Hayat S, Phi N.   +7 more
europepmc   +1 more source

Prediction of Thermomechanical Behavior of Wood-Plastic Composites Using Machine Learning Models: Emphasis on Extreme Learning Machine. [PDF]

Polymers (Basel)
Hua X, Cao Y, Liu B, Yang X, Xu H, Li L, Wu J.   +6 more
europepmc   +1 more source

A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer. [PDF]

Sci Rep
Huang X, Xu A, Liu H, Ye B.
europepmc   +1 more source

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Homo-ELM: fully homomorphic extreme learning machine

International Journal of Machine Learning and Cybernetics, 2020
Extreme learning machine (ELM) as a machine learning method has been successfully applied to many classification problems. However, when applying ELM to classification tasks on the encrypted data in cloud, the classification performance is extremely low. Due to the data encryption, ELM is hard to extract informative features from the encrypted data for
Weiru Wang, Yanfen Gan, Chi-Man Vong, Chuangquan Chen   +3 more
openaire   +1 more source

OP-ELM: Optimally Pruned Extreme Learning Machine

IEEE Transactions on Neural Networks, 2010
In this brief, the optimally pruned extreme learning machine (OP-ELM) methodology is presented. It is based on the original extreme learning machine (ELM) algorithm with additional steps to make it more robust and generic. The whole methodology is presented in detail and then applied to several regression and classification problems.
Sorjamaa, Antti, Bas, Patrick, Simula, Olli, Jutten, Christian, Lendasse, Amaury, Miche, Yoan   +6 more
openaire   +4 more sources

ELM ∗ : distributed extreme learning machine with MapReduce

World Wide Web, 2013
Extreme Learning Machine (ELM) has been widely used in many fields such as text classification, image recognition and bioinformatics, as it provides good generalization performance at a extremely fast learning speed. However, as the data volume in real-world applications becomes larger and larger, the traditional centralized ELM cannot learn such ...
Junchang Xin, Zhiqiong Wang, Chen Chen, Linlin Ding, Guoren Wang, Yuhai Zhao   +5 more
openaire   +1 more source

Hypoglycemia prediction using extreme learning machine (ELM) and regularized ELM

2013 25th Chinese Control and Decision Conference (CCDC), 2013
Hypoglycemia prediction plays an important role for diabetes management. Along with the development of continuous glucose monitoring (CGM) technology, blood glucose prediction becomes possible. Using CGM readings, extreme learning machines (ELM) and regularized ELM (RELM) are implemented in this paper to predict hypoglycemia.
Xue Mo, Youqing Wang, Xiangwei Wu
openaire   +1 more source