Multi-resolution imageprocessing are part of this concept that has a purpose to extracting the detail information of the multi-scale input image. However, in general, to process a multi-scale imagethere are issue th...
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In this paper, a single image multi-scale super-resolution technique is proposed. the concept under study is the learning procedure between steps of amplification in order to predict the next high scale of resolution....
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ADAS (Advanced Driver Assistance systems) algorithms increasingly use heavy imageprocessing operations. To embed this type of algorithms, semiconductor companies offer many heterogeneous architectures. these SoCs (Sy...
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ISBN:
(纸本)9781479989379
ADAS (Advanced Driver Assistance systems) algorithms increasingly use heavy imageprocessing operations. To embed this type of algorithms, semiconductor companies offer many heterogeneous architectures. these SoCs (System on Chip) are composed of different processing units, with different capabilities, and often with massively parallel computing unit. Due to the complexity of these SoCs, predicting if a given algorithm can be executed in real time on a given architecture is not trivial. In fact it is not a simple task for automotive industry actors to choose the most suited heterogeneous SoC for a given application. Moreover, embedding complex algorithms on these systems remains a difficult task due to heterogeneity, it is not easy to decide how to allocate parts of a given algorithm on the different computing units of a given SoC. In order to help automotive industry in embedding algorithms on heterogeneous architectures, we propose a novel approach to predict performances of imageprocessingalgorithms applicable on different types of computing units. Our methodology is able to predict a more or less wide interval of execution time with a degree of confidence using only high level description of algorithms, and a few characteristics of computing units.
the proceedings contain 269 papers. the topics discussed include: high-speed multiview 3D structured light imaging technique;integration of advanced stereo obstacle detection with perspectively correct surround views;...
the proceedings contain 269 papers. the topics discussed include: high-speed multiview 3D structured light imaging technique;integration of advanced stereo obstacle detection with perspectively correct surround views;recreating Van Gogh's original colors on museum displays;modeling long range features from serial section imagery of continuous fiber reinforced composites;the quality of stereo disparity in the polar regions of a stereo panorama;do different radiologists perceive medical images the same way? some insights from representational similarity analysis;the intersection of artificial intelligence and augmented reality;self-calibrated surface acquisition for integrated positioning verification in medical applications;gradient management and algebraic reconstruction for single image super resolution;segmentation-based detection of local defects on printed pages;automated optical inspection for abnormal-shaped packages;towards combining domain knowledge and deep learning for computational imaging;a 360-degrees holographic true 3D display unit using a Fresnel phase plate;and visual analytic process to familiarize the average person with ways to apply machine learning.
Recently, 3D time-of-flight cameras have been developed. the development enables utilization of depthimages in various fields. However, acquired depthimages are corrupted by noise during the image acquisition proces...
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As the development of interactive robots and machines, studies to understand and reproduce facial emotions by computers have become important research areas. For achieving this goal, several deep learning-based facial...
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Stereo matching methods estimate the depth information from stereoscopic images using the characteristics of binocular disparity. We try to find corresponding points from the left and right viewpoint images to obtain ...
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Semi-supervised learning uses underlying relationships in data with a scarcity of ground-truth labels. In this paper, we introduce an uncertainty quantification (UQ) method for graph-based semi-supervised multi-class ...
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images data may contain low resolution characters, and it is not easy to estimate the given low resolution characters. this paper proposed the stochastic model of the low resolution characters and considered the topol...
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ISBN:
(纸本)9781509049172
images data may contain low resolution characters, and it is not easy to estimate the given low resolution characters. this paper proposed the stochastic model of the low resolution characters and considered the topological properties from the color strength of gray scale image.
the evolution of modern sensors for image acquisition brings as much obstacles as many possibilities to obtain multidimensional data with high resolution and rich information. One of the most perceptible destructive f...
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