The proposed method uses a single-source deep instance attention model with parallel branches for joint localization and classification of objects.

May 23, 2021 · We approach this problem from a weakly supervised learning perspective in which the input images correspond to larger neighborhoods around the ...

We propose a weakly supervised learning methodology for the classification of 40 types of trees by using fixed-sized multispectral images with a class label but ...

Multisource image analysis that leverages complementary spectral, spatial, and structural information benefits fine-grained object recognition that aims to ...

Mar 5, 2021 · Abstract. Multisource image analysis that leverages complementary spectral, spatial, and structural information benefits fine-grained object.

Weakly supervised instance attention for multisource fine-grained object recognition with an application to tree species classification.

Multisource image analysis that leverages complementary spectral, spatial, and structural information benefits fine-grained object recognition that aims to ...

We propose a weakly supervised learning methodology for the classification of 40 types of trees by using fixed-sized multispectral images with a class label but ...

Weakly Supervised Instance Attention for Multisource Fine-Grained Object Recognition with an Application to Tree Species Classification.

Weakly supervised instance attention for multisource fine-grained object recognition with an application to tree species classification. Article. Jun 2021 ...