Results 31 to 40 of about 5,782,720 (331)
COMPARISON OF SEVERAL REMOTE SENSING IMAGE CLASSIFICATION METHODS BASED ON ENVI [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 With the development of remote sensing technology and the increasing accuracy of remote sensing images, research on the accuracy of remote sensing classification is becoming more and more important.
X. C. Li +6 more
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5G/B5G Service Classification Using Supervised Learning
Applied Sciences, 2021 The classification of services in 5G/B5G (Beyond 5G) networks has become important for telecommunications service providers, who face the challenge of simultaneously offering a better Quality of Service (QoS) in their networks and a better Quality of ...
Jorge E. Preciado-Velasco +4 more
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Combining Labelled and Unlabelled Data in the Design of Pattern Classification Systems [PDF]
There has been much interest in applying techniques that incorporate knowledge from unlabelled data into a supervised learning system but less effort has been made to compare the effectiveness of different approaches on real world problems and to ...
Gabrys, Bogdan
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Semisupervised Center Loss for Remote Sensing Image Scene Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 High-resolution remote sensing image scene classification is a scene-level classification task. Driven by a wide range of applications, accurate scene annotation has become a hot and challenging research topic.
Jun Zhang +3 more
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ReliaMatch: Semi-Supervised Classification with Reliable Match
Applied Sciences, 2023 Deep learning has been widely used in various tasks such as computer vision, natural language processing, predictive analysis, and recommendation systems in the past decade.
Tao Jiang +4 more
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Classification Uncertainty Minimization-based Semi-supervised Ensemble Learning Algorithm [PDF]
Jisuanji kexue, 2023 Semi-supervised ensemble learning(SSEL) is a combinatorial paradigm by fusing semi-supervised learning and ensemble learning together,which improves the diversity of ensemble learning by introducing unlabeled samples and at the same time solves the ...
HE Yulin, ZHU Penghui, HUANG Zhexue, Fournier-Viger PHILIPPE
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Medical Image Anal., 2022 Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised ...
N. G. Laleh +22 more
semanticscholar +1 more source
Transferability and Hardness of Supervised Classification Tasks [PDF]
IEEE International Conference on Computer Vision, 2019 We propose a novel approach for estimating the difficulty and transferability of supervised classification tasks. Unlike previous work, our approach is solution agnostic and does not require or assume trained models.
A. Tran, Cuong V Nguyen, Tal Hassner
semanticscholar +1 more source
MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classification [PDF]
Annual Meeting of the Association for Computational Linguistics, 2020 This paper presents MixText, a semi-supervised learning method for text classification, which uses our newly designed data augmentation method called TMix.
Jiaao Chen, Zichao Yang, Diyi Yang
semanticscholar +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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