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Designing of FPGA-Based Real Time Spatial Filter of Image Processing
Hilal Tayara,Deok Jin Lee,Kil To Chong 대한기계학회 2014 대한기계학회 춘추학술대회 Vol.2014 No.4
The ability of using reconfigurable hardware like field programmable gate arrays (FPGAs) gives a good way of obtaining high performance for DSP applications like image processing. We present in this paper an efficient hardware implementation of spatial filter which is one of the important step in image processing application. We have used Matlab for designing the architecture and generating Hardware Description Language (HDL) code. The results we obtained were good in term of area and execution time.
Implementation of Coplanar PosIt Algorithm Using Soft-Core Processor (Nios II)
Hilal Tayara,Subbash Panati,Yan Xiaoyi,Kil To Chong 대한전자공학회 2016 대한전자공학회 학술대회 Vol.2016 No.6
Pose estimation is an important step in augmented reality applications and robot localization and navigation. This paper presents fast implementation of coplanar posit algorithm on soft-core processor. The algorithm runs on Nios Ⅱ soft-core processor supplied with floating point hardware for accelerating floating point operations. Taylor series and cubic approximation were used for approximating trigonometric functions. Square root has been approximated using Inverse square root method. High performance has been achieved by the designed system.
Identification of prokaryotic promoters and their strength by integrating heterogeneous features
Tayara, Hilal,Tahir, Muhammad,Chong, Kil To Elsevier 2020 Genomics Vol.112 No.2
<P><B>Abstract</B></P> <P>The promoter is a regulatory DNA region and important for gene transcriptional regulation. It is located near the transcription start site (TSS) upstream of the corresponding gene. In the post-genomics era, the availability of data makes it possible to build computational models for robustly detecting the promoters as these models are expected to be helpful for academia and drug discovery. Until recently, developed models focused only on discriminating the sequences into promoter and non-promoter. However, promoter predictors can be further improved by considering weak and strong promoter classification. In this work, we introduce a hybrid model, named iPSW(PseDNC-DL), for identification of prokaryotic promoters and their strength. It combines a convolutional neural network with a pseudo-di-nucleotide composition (PseDNC). The proposed model iPSW(PseDNC-DL) has been evaluated on the benchmark datasets and outperformed the current state-of-the-art models in both tasks namely promoter identification and promoter strength identification. The developed tool iPSW(PseDNC-DL) has been constructed in a web server and made freely available at https://home.jbnu.ac.kr/NSCL/PseDNC-DL.htm </P> <P><B>Highlights</B></P> <P> <UL> <LI> Computational predictor is developed for prediction of prokaryotic promoters and their strength. </LI> <LI> Deep learning approach is used. </LI> <LI> Integrating deep learning features with pseudo-di-nucleotide composition (PseDNC). </LI> <LI> Achieved promising outcomes than existing methods. </LI> </UL> </P>
Fixed-point Harris Corner Detection Implementation on FPGA Using MATLAB HDL Coder
Hilal Tayara,Kil To Chong 대한전기학회 2015 대한전기학회 학술대회 논문집 Vol.2015 No.4
Harris corner detection is considered as an important step in many image processing algorithms for extracting the features of the objects in the foreground. In this paper, fixed point architecture of Harris corner detection will be introduced on FPGA using Simulink and HDL coder and comparison between floating and fixed point results will be discussed.
Fixed-point Harris Corner Detection Implementation on FPGA Using MATLAB HDL Coder
Hilal Tayara,Kil To Chong 대한전기학회 2015 정보 및 제어 심포지엄 논문집 Vol.2015 No.4
Harris corner detection is considered as an important step in many image processing algorithms for extracting the features of the objects in the foreground. In this paper, fixed point architecture of Harris corner detection will be introduced on FPGA using Simulink and HDL coder and comparison between floating and fixed point results will be discussed.