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In recent years, object detection has been more frequently integrated with other vision processing functions, acting for acquisition of region of interest and is widely adopted in portable devices such as digital camera capable for automatic focusing on faces. In applications targeting those devices, limitations in both hardware resources and power supply mean an efficient utilization of hardware...
Reconfigurable computers have started to appear in the HPC landscape, albeit at a slow pace. Adoption is still being hindered by the design methodologies and slow implementation cycles. Recently, methodologies based on High Level Synthesis (HLS) have begun to flourish and the reconfigurable supercomputing community is slowly adopting these techniques. In this paper we took a geophysics application...
Artificial Neural Networks (ANN) have proven to be effective in solving various emerging biomedical applications through specialized ANN hardware. Unfortunately, these ANN-based biomedical systems are increasingly vulnerable to both transient and permanent faults, potentially imposing serious threats to human well-being. Inspired by the self-healing and self-recovery mechanisms of the human nervous...
Adaptive systems have the ability to respond to environmental conditions, by modifying their processing at runtime. While this is easy to do software systems, modern algorithms can be computationally expensive, requiring powerful processors. At the same time hardware is not as flexible. Field programmable gate arrays (FPGAs) are recognised as being suitable for adaptive systems implementation, due...
Least Squares Support Vector Machines(LS-SVM), which is an efficient supervised learning tool, has been widely applied to real-time on-line data processing in many fields. However, the on-line training of LS-SVM always suffers from huge computation which greatly limits its practicability especially in embedded systems. By leveraging the flexibility and high degree parallelism offered by reconfigurable...
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