Results 41 to 50 of about 2,740,047 (370)
IEEE Transactions on Image Processing, 2022 The difficulties of obtaining sufficient labeled samples have always been one of the factors hindering deep learning models from obtaining high accuracy in hyperspectral image (HSI) classification.
Kuiliang Gao +3 more
semanticscholar +1 more source
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
doaj +1 more source
Unsupervised Exemplar-Based Learning for Improved Document Image Classification
IEEE Access, 2019 Many recent state-of-the-art approaches for document image classification are based on supervised feature learning that requires a large amount of labeled training data.
Sherif Abuelwafa +2 more
doaj +1 more source
Supervised and Unsupervised Neural Approaches to Text Readability
Computational Linguistics, 2021 We present a set of novel neural supervised and unsupervised approaches for determining the readability of documents. In the unsupervised setting, we leverage neural language models, whereas in the supervised setting, three different neural ...
Matej Martinc +2 more
doaj +1 more source
Contrastive Learning for Sports Video: Unsupervised Player Classification [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 We address the problem of unsupervised classification of players in a team sport according to their team affiliation, when jersey colours and design are not known a priori.
Maria Koshkina +2 more
semanticscholar +1 more source
Predicting Category Intuitiveness With the Rational Model, the Simplicity Model, and the Generalized Context Model [PDF]
, 2009 Naïve observers typically perceive some groupings for a set of stimuli as more intuitive than others. The problem of predicting category intuitiveness has been historically considered the remit of models of unsupervised categorization.
Bailey, T. M., Pothos, E. M.
core +1 more source
Terrain classification for a quadruped robot [PDF]
, 2013 Using data retrieved from the Puppy II robot at the University of Zurich (UZH), we show that machine learning techniques with non-linearities and fading memory are effective for terrain classification, both supervised and unsupervised, even with a ...
Degrave, Jonas +4 more
core +1 more source
ACCURACY OF UNSUPERVISED CLASSIFICATION TO DETERMINE CORAL HEALTH USING SPOT-6 AND SENTINEL-2A [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 Characteristics of corals spectral from different species are expected to have optically different characters. The aims of this research are to compare unsupervised classification between IsoData and K-Means methods with Lyzenga application, and to ...
N. Nurdin +7 more
doaj +1 more source
Invariant Information Clustering for Unsupervised Image Classification and Segmentation [PDF]
IEEE International Conference on Computer Vision, 2018 We present a novel clustering objective that learns a neural network classifier from scratch, given only unlabelled data samples. The model discovers clusters that accurately match semantic classes, achieving state-of-the-art results in eight ...
Xu Ji, A. Vedaldi, João F. Henriques
semanticscholar +1 more source
Missing Value Imputation With Unsupervised Backpropagation [PDF]
, 2013 Many data mining and data analysis techniques operate on dense matrices or complete tables of data. Real-world data sets, however, often contain unknown values.
Gashler, Michael S. +3 more
core +1 more source