Superpixel contracted graph-based learning for hyperspectral image classification
P Sellars, AI Aviles-Rivero… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
A central problem in hyperspectral image (HSI) classification is obtaining high classification
accuracy when using a limited amount of labeled data. In this article we present a novel …
accuracy when using a limited amount of labeled data. In this article we present a novel …
Superpixel-based multi-scale multi-instance learning for hyperspectral image classification
S Huang, Z Liu, W Jin, Y Mu - Pattern Recognition, 2024 - Elsevier
Superpixels can define meaningful local regions within a hyperspectral image (HSI) and
have become the building blocks of various HSI classification methods. The superpixels in …
have become the building blocks of various HSI classification methods. The superpixels in …
Visual classification of lettuce growth stage based on morphological attributes using unsupervised machine learning models
J Alejandrino, R Concepcion… - 2020 IEEE REGION …, 2020 - ieeexplore.ieee.org
Food shortage is a serious problem facing the world and is prevalent in urban areas. The
scarcity of food is mainly caused by crop failure. Environmental factors offered by the rural …
scarcity of food is mainly caused by crop failure. Environmental factors offered by the rural …
DRFL-VAT: Deep representative feature learning with virtual adversarial training for semisupervised classification of hyperspectral image
J Chen, Y Wang, L Zhang, M Liu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
While deep learning algorithms have achieved good results in hyperspectral image (HSI)
classification, several supervised classification algorithms rely on a large number of labeled …
classification, several supervised classification algorithms rely on a large number of labeled …
Novel semi-supervised hyperspectral image classification based on a superpixel graph and discrete potential method
Y Zhao, F Su, F Yan - Remote Sensing, 2020 - mdpi.com
Hyperspectral image (HSI) classification plays an important role in the automatic
interpretation of the remotely sensed data. However, it is a non-trivial task to classify HSI …
interpretation of the remotely sensed data. However, it is a non-trivial task to classify HSI …
Adaptive graph learning for semi-supervised self-paced classification
L Chen, J Lu - Neural Processing Letters, 2022 - Springer
Semi-supervised learning techniques have been attracting increasing interests in many
machine learning fields for its effectiveness in using labeled and unlabeled samples …
machine learning fields for its effectiveness in using labeled and unlabeled samples …