high performance computing on graphics processing units: hgpu.org

Publication: Submissions will be peer reviewed and evaluated based on originality, relevance to conference, contributions, and presentation. Selected papers of ICICA 2016 will be published in one of the below Journals: * Journal of Computers (ISSN: 1796-203X) Indexing/Abstracting: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH’s Periodicals Directory, WorldCat, CNKI,etc. * Journal of Advances in Information Technology […]

Topics: VLSI Design & Testing Low Power VLSI Image & Signal Processing Grid & Cloud Computing Routing & Optimization Techniques Wired & Wireless Communication Sensor Networks & Network Security Mobile Communication & Computing High Speed Communication Networks Embedded System Intelligent Controllers Modeling & Simulation System Identification Advanced Control Systems Expert Systems Biomedical Instrumentation Process Control […]

Topics: • Remote Sensing • Innovative Algorithms • Automated feature extraction • Object extraction • Point cloud processing • 3D scene reconstruction • Spatio-temporal data fusion • Range image processing • Photogrammetric computer vision • Multi-scale segmentation • Support Vector Machine classifiers • Random forest classifiers • Marked point process extractors • Sparse and redundant […]

Publication: Submissions will be peer reviewed and evaluated based on originality, relevance to conference, contributions, and presentation. Selected papers of ICICA 2016 will be published in one of the below Journals: * Journal of Computers (ISSN: 1796-203X) Indexing/Abstracting: DBLP, EBSCO, DOAJ, ProQuest, INSPEC, ULRICH’s Periodicals Directory, WorldCat, CNKI,etc. * International Journal of Modeling and Optimization […]

Protein tertiary structure prediction (PSP) is one of the most challenging problems in bioinformatics. Different methods have been introduced to solve this problem so far, but PSP is computationally intensive and belongs to the NP-hard class. One of the best solutions to accelerate PSP is the use of a massively parallel processing architecture, such graphical […]

In this paper, we present convolutional patch networks, which are convolutional (neural) networks (CNN) learned to distinguish different image patches and which can be used for pixel-wise labeling. We show how to easily learn spatial priors for certain categories jointly with their appearance. Experiments for urban scene understanding demonstrate state-of-the-art results on the LabelMeFacade dataset. […]

Parallel CPU implementations of a viewshed algorithm using both multithreading and SIMD vectorization and GPU implementations were implemented and compared in this study. The results show that parallelism is essential for achieving good performance on a CPU, and that data transfer can be partly overlapped by computations to hide some of the overheads in GPU […]

Image-based sequence recognition has been a long-standing research topic in computer vision. In this paper, we investigate the problem of scene text recognition, which is among the most important and challenging tasks in image-based sequence recognition. A novel neural network architecture, which integrates feature extraction, sequence modeling and transcription into a unified framework, is proposed. […]

Greedy Restrictive Boltzmann Machines yield an fairly low 0.72% error rate on the famous MNIST database of handwritten digits. All that was required to achieve this result was a high number of hidden layers consisting of many neurons, and a graphics card to greatly speed up the rate of learning.

The Deep Boltzmann Machine (DBM) has been proved to be one of the most effective machine learning generative models in discriminative tasks. They’ve been able to overcome other generative, and even discriminative models, on relatively simple tasks, such as digits recognition, and also on more complex tasks such as simple objects recognition. However, there’re only […]

The increasing adoption of Graphic Process Unit (GPU) to computation-intensive workloads has stimulated a new computing paradigm called GPU cloud (e.g., Amazon’s GPU Cloud), which necessitates the sharing of GPU resources to multiple tenants in a cloud. However, state-of-the-art GPU virtualization techniques such as gVirt still suffer from non-trivial performance overhead for graphics memory-intensive workloads […]

The aim of this thesis is to explore different methods for helping computers interpret the real world visually, investigate solutions to those methods offered by the open-sourced computer vision library, OpenCV, and implement some of these in a Raspberry Pi based application for detecting and keeping track of objects. The main focus rests on the […]