Feb 28, 2019 · In this work, we proposed a salient object detection model on hyperspectral images by applying manifold ranking (MR) on self-supervised ...

Salient object detection on hyperspectral images using features learned from unsupervised segmentation task. This pytorch code was implemented by Nevrez ...

Experimental evaluations demonstrated that proposed saliency detection algorithm on hyperspectral images is outperforming state-of-the-arts hyperspectrals ...

Jul 24, 2024 · In this paper, we propose a high-level feature-based salient object detection algorithm. The manifold ranking is applied on the self-supervised CNN features.

In this work, we proposed a salient object detection model on hyperspectral images by applying manifold ranking (MR) on self-supervised Convolutional Neural ...

... Imamoglu et al. [13] proposed a salient object detection technique for hyperspectral images using unsupervised segmentation methodology with CNN. Since HSI ...

In this work, we proposed a salient object detection model on hyperspectral images by applying manifold ranking (MR) on self-supervised Convolutional Neural ...

Mar 1, 2021 · In this paper, we propose a salient object detection model on hyperspectral images in wireless network by applying saliency optimization to convolutional ...

The proposed methodology incorporates Extended Morphology (EMP) followed by a CNN to utilize the information from nearby pixels and high-level features ...

HS-SOD is a hyperspectral salient object detection dataset with a collection of 60 hyperspectral images with their respective ground-truth binary images.