This work develops highly efficient algorithms for analyzing large images. Applications include object-based change detection and screening. The algorithms are 10-100 times as fast as existing software, sometimes even outperforming FGPA/GPU hardware, because they are designed to suit the computer architecture. This thesis describes the implementation details and the underlying algorithm engineering methodology, so that both may also be applied to other applications
The theme of this work is manipulating large data in the field of computer graphics. Generally, larg...
Designing parallel models that fully utilize the computation capabilities of Graphics Processing Uni...
Image classification is a extensively studied problem that lies at the heart of computer vision. How...
This work develops highly efficient algorithms for analyzing large images. Applications include obje...
This work develops highly efficient algorithms for analyzing large images. Applications include obje...
This thesis examines the application of massively parallel processing to the computationally intensi...
I focus on designing efficient and adaptive algorithms for object detection from large scale image a...
Abstract---Enormous amount of images are uploaded and used via internet and this ratio is still dras...
AbstractIndustrial image processing tasks, especially in the domain of optical metrology, are becomi...
Click on the DOI link to access the article (may not be free).Traditional methods for processing lar...
This article describes expediency of using a graphics processing unit (GPU) in big data processing i...
In this paper we present the architecture, the algorithm and the implementation of an advanced imagi...
Spatial resolution is a very important quality metric to measure digital images. The higher the reso...
Computational requirements for computer vision algorithms have been increasing dramatically at a rat...
Algorithms for recognition and retrieval tasks generally call for both speed and accuracy. When scal...
The theme of this work is manipulating large data in the field of computer graphics. Generally, larg...
Designing parallel models that fully utilize the computation capabilities of Graphics Processing Uni...
Image classification is a extensively studied problem that lies at the heart of computer vision. How...
This work develops highly efficient algorithms for analyzing large images. Applications include obje...
This work develops highly efficient algorithms for analyzing large images. Applications include obje...
This thesis examines the application of massively parallel processing to the computationally intensi...
I focus on designing efficient and adaptive algorithms for object detection from large scale image a...
Abstract---Enormous amount of images are uploaded and used via internet and this ratio is still dras...
AbstractIndustrial image processing tasks, especially in the domain of optical metrology, are becomi...
Click on the DOI link to access the article (may not be free).Traditional methods for processing lar...
This article describes expediency of using a graphics processing unit (GPU) in big data processing i...
In this paper we present the architecture, the algorithm and the implementation of an advanced imagi...
Spatial resolution is a very important quality metric to measure digital images. The higher the reso...
Computational requirements for computer vision algorithms have been increasing dramatically at a rat...
Algorithms for recognition and retrieval tasks generally call for both speed and accuracy. When scal...
The theme of this work is manipulating large data in the field of computer graphics. Generally, larg...
Designing parallel models that fully utilize the computation capabilities of Graphics Processing Uni...
Image classification is a extensively studied problem that lies at the heart of computer vision. How...