Results 51 to 60 of about 5,782,720 (331)
Weakly supervised classification in high energy physics
Journal of High Energy Physics, 2017 As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations.
Lucio Mwinmaarong Dery +3 more
doaj +1 more source
Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours
AAAI Conference on Artificial Intelligence, 2017 Due to the efficiency of learning relationships and complex structures hidden in data, graph-oriented methods have been widely investigated and achieve promising performance in multi-view learning.
F. Nie, Guo-Hao Cai, Xue-Long Li
semanticscholar +1 more source
Determining the accuracy in image supervised classification problems [PDF]
, 2011 A large number of accuracy measures for crisp supervised classification have been developed in supervised image classification literature. Overall accuracy, Kappa index, Kappa location, Kappa histo and user accuracy are some well-known examples.
Gómez González, Daniel +3 more
core +1 more source
Remote Sensing, 2022 Deep learning methods have become an integral part of computer vision and machine learning research by providing significant improvement performed in many tasks such as classification, regression, and detection. These gains have been also observed in the
Paul Berg, Minh-Tan Pham, Nicolas Courty
doaj +1 more source
A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT
IEEE Transactions on Medical Imaging, 2020 Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-CoV-2.
Xing-Gang Wang +7 more
semanticscholar +1 more source
Watersheds for Semi-Supervised Classification [PDF]
IEEE Signal Processing Letters, 2019 Watershed technique from mathematical morphology (MM) is one of the most widely used operators for image segmentation. Recently watersheds are adapted to edge weighted graphs, allowing for wider applicability. However, a few questions remain to be answered – How do the boundaries of the watershed operator behave?
Aditya Challa +3 more
openaire +2 more sources
Self-Supervised Learning for Solar Radio Spectrum Classification
Universe, 2022 Solar radio observation is an important way to study the Sun. Solar radio bursts contain important information about solar activity. Therefore, real-time automatic detection and classification of solar radio bursts are of great value for subsequent solar
Siqi Li +4 more
doaj +1 more source
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
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
Fingerprint Liveness Detection in the Presence of Capable Intruders
Sensors, 2015 Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the
Ana F. Sequeira, Jaime S. Cardoso
doaj +1 more source