Results 261 to 270 of about 3,746,359 (297)

Self-Supervised Cloud Classification

Artificial Intelligence for the Earth Systems
Abstract Low-level marine clouds play a pivotal role in Earth’s weather and climate through their interactions with radiation, heat and moisture transport, and the hydrological cycle. These interactions depend on a range of dynamical and microphysical processes that result in a broad diversity of cloud types and spatial structures, and a comprehensive ...
Andrew Geiss, Matthew W. Christensen, Adam C. Varble, Tianle Yuan, Hua Song   +4 more
openaire   +1 more source

Supervised Classification Techniques

1986
Supervised classification is the technique most often used for the quantitative analysis of remote sensing image data. At its core is the concept of segmenting the spectral domain into regions that can be associated with the ground cover classes of interest to a particular application. In practice those regions may sometimes overlap.
openaire   +1 more source

Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms

Neural Computation, 1998
Thomas G. Dietterich
semanticscholar   +1 more source

ChestX-ray: Hospital-Scale Chest X-ray Database and Benchmarks on Weakly Supervised Classification and Localization of Common Thorax Diseases

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, 2019
Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, M. Bagheri, R. Summers   +5 more
semanticscholar   +1 more source

Supervised Learning for Classification

2005
Supervised local tangent space alignment is proposed for data classification in this paper. It is an extension of local tangent space alignment, for short, LTSA, from unsupervised to supervised learning. Supervised LTSA is a supervised dimension reduction method.
Hongyu Li, Wenbin Chen, I-Fan Shen
openaire   +1 more source

Supervised Machine Learning—Classification

2017
Classification and prediction are two important methods of data analysis used to find patterns in data. Classification predicts the categorical class (or discrete values), whereas regression and other models predict continuous valued functions. For example, a classification model may be built to predict the results of a credit-card application approval
Umesh R. Hodeghatta, Umesh Nayak
openaire   +1 more source

A survey of multi-label classification based on supervised and semi-supervised learning

International Journal of Machine Learning and Cybernetics, 2022
Meng Han, Hongxin Wu, Zhiqiang Chen, Muhan Li, Xilong Zhang   +4 more
semanticscholar   +1 more source

Supervised Classification

2018
Stacy A. C. Nelson, Siamak Khorram
openaire   +2 more sources

Weakly Supervised Text Classification

2019
Deep neural networks are gaining increasing popularity for the classic text classification task, due to their strong expressive power and less requirement for feature engineering. Despite such attractiveness, neural text classification models suffer from the lack of training data in many real-world applications. Although many semi-supervised and weakly-
openaire   +1 more source

Supervised Classification Algorithms in Machine Learning: A Survey and Review

Advances in Intelligent Systems and Computing, 2019
P. C. Sen, Mahimarnab Hajra, Mitadru Ghosh   +2 more
semanticscholar   +1 more source