Results 61 to 70 of about 6,403,045 (365)
Recurrent Attentional Networks for Saliency Detection
, 2016 Convolutional-deconvolution networks can be adopted to perform end-to-end saliency detection. But, they do not work well with objects of multiple scales.
Kuen, Jason, Wang, Gang, Wang, Zhenhua
core +1 more source
A DETECTION METHOD OF ARTIFICIAL AREA FROM HIGH RESOLUTION REMOTE SENSING IMAGES BASED ON MULTI SCALE AND MULTI FEATURE FUSION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 In order to solve the problem of automatic detection of artificial objects in high resolution remote sensing images, a method for detection of artificial areas in high resolution remote sensing images based on multi-scale and multi feature fusion is ...
P. Li +6 more
doaj +1 more source
Saliency-Based Multiple Region of Interest Detection From a Single 360° Image
IEEE Access, 2022 360° images are informative – it contains omnidirectional visual information around the camera. However, the areas that cover a 360° image is much larger than the human’s field of view, therefore important information in ...
Yuuki Sawabe +2 more
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Integrated Deep and Shallow Networks for Salient Object Detection
, 2017 Deep convolutional neural network (CNN) based salient object detection methods have achieved state-of-the-art performance and outperform those unsupervised methods with a wide margin.
Dai, Yuchao +4 more
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Image summaries using database saliency [PDF]
ACM SIGGRAPH ASIA 2009 Posters, 2009 It is useful to have a small set of representative images from a database of thousands of images to summarize its content. There are two key aspects of such image summaries: how to generate them and how to present them. We address both issues. We extend the idea of image saliency to databases and introduce the notion of database saliency. We argue that
Radhakrishna Achanta +3 more
openaire +1 more source
Inaccurate Supervised Saliency Detection Based on Iterative Feedback Framework
IEEE Access, 2020 Machine learning based bottom-up saliency detection (MLBU) methods are very popular recently. These MLBU methods firstly use prior knowledge to select some regions from the given image as training samples and label them. Based on training set, a saliency
Yu Pang +4 more
doaj +1 more source
Visual Saliency Models for Text Detection in Real World. [PDF]
PLoS ONE, 2014 This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose.
Renwu Gao +4 more
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IEEE Access, 2022 Techniques for detecting salient objects mimic human behavior by recognizing the most noticeable parts of images as objects. Salient object detection has attracted many researchers’ attention nowadays for various computer vision and pattern ...
Bhagyashree V. Lad +2 more
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Multi-scale Discriminant Saliency with Wavelet-based Hidden Markov Tree Modelling
, 2013 The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between centre and surround classes.
Ang, Kenneth Li-Minn +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background B‐acute lymphoblastic leukemia (B‐ALL) is the most common pediatric cancer, and while most children in high‐resource settings are cured, therapy carries risks for long‐term toxicities. Understanding parents’ concerns about these late effects is essential to guide anticipatory support and inform evolving therapeutic approaches ...
Kellee N. Parker +7 more
wiley +1 more source