Results 21 to 30 of about 102,109 (257)
DE-ELM-SSC+：Semi-supervised Classification Algorithm
Jisuanji kexue yu tansuo, 2020 The combinations of evolutionary algorithms (EA) and analytical methods have been extensively studied in the fields of machine learning in recent years. This paper focuses on how to combine a differential evolution (DE) algorithm with the semi-supervised
PANG Jun, HUANG Heng, ZHANG Shou, SHU Zhiliang, ZHAO Yuhai
doaj +1 more source
Semi-Supervised Learning for Image Classification using Compact Networks in the BioMedical Context [PDF]
, 2022 Background and objectives: The development of mobile and on the edge appli-cations that embed deep convolutional neural models has the potential to revolutionisebiomedicine.
Díaz-Pinto, Andrés +5 more
core
Semi-Supervised DEGAN for Optical High-Resolution Remote Sensing Image Scene Classification
Remote Sensing, 2022 Semi-supervised methods have made remarkable achievements via utilizing unlabeled samples for optical high-resolution remote sensing scene classification.
Jia Li +4 more
doaj +1 more source
CBARS: cluster based classification for activity recognition systems [PDF]
, 2012 Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition.
Gaber, Mohamed Medhat +11 more
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Lithofacies Classification Using Supervised and Semi-Supervised Machine Learning Approach [PDF]
, 2021 The machine learning approach can help Geoscientists do their work in well log analysis to developing the oil and gas field. Prediction categorical or numerical response variable using a set of predictor variables supervises and semi-supervises learning ...
Hardanto, Lilik T.; Department of Computer Science, Binus University, Jakarta, 11530, Indonesia +1 more
core +1 more source
Convex Multiview Semi-Supervised Classification
, 2017 In many practical applications, there are a great number of unlabeled samples available, while labeling them is a costly and tedious process. Therefore, how to utilize unlabeled samples to assist digging out potential information about the problem is ...
Feiping Nie +5 more
core +1 more source
Self-labeling techniques for semi-supervised time series classification: an empirical study [PDF]
An increasing amount of unlabeled time series data available render the semi-supervised paradigm a suitable approach to tackle classification problems with a reduced quantity of labeled data.
Triguero, Isaac +4 more
core +1 more source
EURASIP Journal on Wireless Communications and Networking, 2020 With the advent of the era of network information, the amount of data in network information is getting larger and larger, and the classification of data becomes particularly important.
Yang Gang +5 more
doaj +1 more source
FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 more
wiley +1 more source
FEBS Letters, EarlyView.An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley +1 more source