Dec 21, 2020 · In this paper, we propose a novel approach that is based on multiscale segmentation and fuzzy broad learning. The core idea of our method is to ...
In this paper, we propose a novel approach that is based on multiscale segmentation and fuzzy broad learning. The core idea of our method is to segment the ...
This paper proposes a novel approach that is significantly faster than most of deep learning-based saliency detection algorithms, in terms of training and ...
In this paper, we propose a novel approach that is based on multiscale segmentation and fuzzy broad learning. The core idea of our method is to segment the ...
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The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks.
Missing: Fuzzy | Show results with:Fuzzy
We propose an algorithm for salient object detection (SOD) based on multi-scale graph ranking and iterative local–global object refinement.
Conventional approaches exploit low-level features and some heuristics to detect salient objects, containing local contrast-based, diffusion-based, Bayesian ...
Missing: Multiscale | Show results with:Multiscale
Aug 10, 2023 · Salient target detection involves detecting and segmenting the most noticeable object area in an image, making it a two-stage visual task.
A regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence ...
Abstract. Many salient object detection (SOD) methods based on convolutional neural networks utilize spatial frequency information from images to obtain salient ...
Missing: Fuzzy Broad