Search Results for: D

Detecting Dominant Vanishing Points in Natural Scenes

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Abstract: Linear perspective is widely used in landscape photography to create the impression of depth on a 2D photo. Automated understanding of linear perspective in landscape photography has several real-world applications, including aesthetics assessment, image retrieval, and on-site feedback for photo composition, yet adequate automated understanding has been elusive. We address this problem by detecting […]

Shape matching for automated bow echo detection

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Abstract: Severe weather conditions cause enormous amount of damages around the globe. Bow echo patterns in radar images are associated with a number of these destructive thunderstorm conditions such as damaging winds, hail and tornadoes. They are detected manually by meteorologists. In this paper, we propose an automatic framework to detect these patterns with high […]

Vanishing Point Detection in Photo Composition Analysis

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Abstract: Linear perspective is widely used in landscape photography to create the impression of depth on a 2D photo. Automated understanding of the use of linear perspective in landscape photography has a number of real-world applications, including aesthetics assessment, image retrieval, and on-site feedback for photo composition. We address this problem by detecting vanishing points […]

Chinese Academy of Sciences

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From April 2016 to June 2016, I was a visiting researcher at Chinese Academy of Sciences (CAS) in Beijing, China. Thanks to all people who accompanied me during my visit. 1st row (standing): Hoho, Yu Huang, Hou Huang, Xikun, FeiFei, Zhang Pan, Shengluan 2nd row (seated): SM Zhang, Lu Ruqian, me, Ju Wang. frash 🙂

Stochastic Modeling and Optimization of Stragglers

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Abstract: MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This paper analytically shows that the stochastic behavior of the servers has a negative […]

Node Architecture and Cloud Workload Characteristics Analysis

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Abstract The combined impact of node architecture and workload characteristics on off-chip network traffic with performance/cost analysis has not been investigated before in the context of emerging cloud applications. Motivated by this observation, this paper performs a thorough characterization of twelve cloud workloads using a full-system datacenter simulation infrastructure. We first study the inherent network […]

Optimal Scheduling in Parallel Programming Frameworks

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FORK-JOIN QUEUE MODELING AND OPTIMAL SCHEDULING IN PARALLEL PROGRAMMING FRAMEWORKS ABSTRACT MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This thesis analytically […]

Towards Stochastically Optimizing Data Computing Flows

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Abstract: With rapid growth in the amount of unstructured data produced by memory-intensive applications, large scale data analytics has recently attracted increasing interest. Processing, managing and analyzing this huge amount of data poses several challenges in cloud and data center computing domain. Especially, conventional frameworks for distributed data analytics are based on the assumption of […]

Big Data Computing: Modeling and Optimization

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Abstract: MapReduce framework is widely used to parallelize batch jobs since it exploits a high degree of multi-tasking to process them. However, it has been observed that when the number of servers increases, the map phase can take much longer than expected. This thesis analytically shows that the stochastic behavior of the servers has a […]

Blind detection of low-rate embedding

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Abstract: Steganalysis of least significant bit (LSB) embedded images in spatial domain has been investigated extensively over the past decade and most well-known LSB steganography methods have been shown to be detectable. However, according to the latest findings in the area, two major issues of very low-rate (VLR) embedding and content-adaptive steganography have remained hard […]