Results 211 to 220 of about 12,627 (258)

Instance-level quantitative saliency in multiple sclerosis lesion segmentation. [PDF]

Sci Rep
Spagnolo F, Molchanova N, Cuadra MB, Ocampo-Pineda M, Melie-Garcia L, Granziera C, Andrearczyk V, Depeursinge A.   +7 more
europepmc   +1 more source

Fault-Tolerant Control of AGVs via Deep Feature Enhancement and Multi-Source Verification in Complex Industrial Environments. [PDF]

Sensors (Basel)
Zhou Y, Peng S, Wang Y, Zhou N, Shan F.
europepmc   +1 more source

Saliency Tree: A Novel Saliency Detection Framework [PDF]

IEEE Transactions on Image Processing, 2014
This paper proposes a novel saliency detection framework termed as saliency tree. For effective saliency measurement, the original image is first simplified using adaptive color quantization and region segmentation to partition the image into a set of primitive regions. Then, three measures, i.e., global contrast, spatial sparsity, and object prior are
Olivier Le Meur, Zhi Liu, Wenbin Zou
exaly   +5 more sources

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Exemplar-based image saliency and co-saliency detection

Neurocomputing, 2020
Abstract Image saliency and co-saliency detection that aim to detect salient objects in an image or common salient objects in a group of images are import in computer vision. Researchers often treat saliency and co-saliency as two separate problems.
Yan Xing, Rui Huang, Wei Feng
exaly   +2 more sources

Saliency Detection Based on Weighted Saliency Probability

2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), 2019
The key to computer-based image recognition is to distinguish salient objects from the image background. However, it is still challenging to detect salient region when an object significantly touches the image boundaries. In this study, we present a novel salient region detection method based on a color space volume and a novel weighted saliency ...
Zuoyong Li, Taotao Lai, Xiaogen Zhou
openaire   +1 more source

Saliency detection for stereoscopic video

Proceedings of the 4th ACM Multimedia Systems Conference, 2013
We present a novel system for automatically detecting salient image regions in stereoscopic videos. Our proposed algorithm considers information based on three dimensions: salient colors in individual frames, salient information derived from camera and object motion, and depth saliency.
Dittrich, Torben, Kopf, Stephan, Schaber, Philipp, Guthier, Benjamin, Effelsberg, Wolfgang   +4 more
openaire   +2 more sources

Histograms of Salience for Pedestrian Detection

Proceedings of International Conference on Internet Multimedia Computing and Service, 2014
Pedestrian detection has been seen huge progress in recent years, much thanks to the Histograms of Oriented Gradients (HOG) features. However, this method (HOG and SVM) has a large number of false detections. To conquer the problem, we provide an affirmative answer by proposing and investigating a salience representation for pedestrian detection ...
Yuanyuan Nan, Chao Liang 0001, Wenhua Fang, Xiao Wang 0029, Yuhong Yang 0001, Jun Chen 0001   +5 more
openaire   +1 more source

Sparse-Distinctive Saliency Detection

IEEE Signal Processing Letters, 2015
In this letter, we propose a novel saliency model for saliency detection, named sparse-distinctive (SD) saliency model. Different from the existing models that only consider sparsity or distinctness of image, the proposed model computes saliency based on sparsity and distinctness.
Yongkang Luo 0001, Peng Wang 0024, Wenjun Zhu, Hong Qiao   +3 more
openaire   +1 more source

Human-Centered Saliency Detection

IEEE Transactions on Neural Networks and Learning Systems, 2016
We introduce a new concept for detecting the saliency of 3-D shapes, that is, human-centered saliency (HCS) detection on the surface of shapes, whereby a given shape is analyzed not based on geometric or topological features directly obtained from the shape itself, but by studying how a human uses the object.
Zhenbao Liu, Xiao Wang 0025, Shuhui Bu
openaire   +2 more sources

Sparse likelihood saliency detection

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
This paper addresses the problem of detection salient regions in images by exploiting the redundancy in image patches. We assume that redundant patches are more likely to be sparsely represented by other patches in the image while salient patches are not. Such sparse likelihood can be measured via L1-minimization by finding the sparse representation of
Hoang, Minh Chau, Rajan, Deepu
openaire   +2 more sources