Ultra fast cnn based Hardware Computing Platform Concepts for adas visual Sensors and Evolutionary Mobile Robots




Download 3,22 Mb.
Pdf ko'rish
bet75/81
Sana16.05.2024
Hajmi3,22 Mb.
#238917
1   ...   71   72   73   74   75   76   77   78   ...   81
Bog'liq
Alireza Fasih

Selective power-down for high performance CPU/system
. 1995, Google 
Patents. 
21. 
Chhugani, J., et al., 
Efficient implementation of sorting on multi-core SIMD CPU 
architecture.
Proceedings of the VLDB Endowment, 2008. 1(2): p. 1313-1324. 
22. 
White, H., 
Artificial neural networks: approximation and learning theory
. 1992: 
Blackwell Publishers, Inc. Cambridge, MA, USA. 
23. 
Hagan, M.T., et al., 
Neural network design
. 1996: PWS Boston, MA. 
24. 
Agatonovic-Kustrin, S. and R. Beresford, 
Basic concepts of artificial neural network 
(ANN) modeling and its application in pharmaceutical research.
Journal of 
pharmaceutical and biomedical analysis, 2000. 22(5): p. 717-727. 
25. 
Albó-Canals, J., et al. 
An efficient FPGA implementation of a DT-CNN for small image 
gray-scale pre-processing
. 2009: IEEE. 
26. 
Toledo, F.J., et al., 
Image processing with CNN in a FPGA-based augmented reality 
system for visually impaired people.
Computational Intelligence and Bioinspired 
Systems, 2005: p. 906-912. 
27. 
Ruaro, M.E., P. Bonifazi, and V. Torre, 
Toward the neurocomputer: Image processing 
and pattern recognition with neuronal cultures.
Biomedical Engineering, IEEE 
Transactions on, 2005. 52(3): p. 371-383. 
28. 
Ham, F.M. and I. Kostanic, 
Principles of neurocomputing for science and engineering

2000: McGraw-Hill Higher Education. 
29. 
Gonzalez, R.C., R.E. Woods, and S.L. Eddins, 
Digital image processing using MATLAB

2004: Pearson Education India. 
30. 
Fasih, A., et al. 
New computational modeling for solving higher order ODE based on 
FPGA
: IEEE. 
31. 
Fasih, A., et al., 
An Ultra-fast and Adaptive Framework for FPGA-Based Real-Time 
Machine Vision for Advanced Driver Assistance Systems: a CNN-Based Processing 
Architec-ture. 
32. 
Aspray, W., 
Computing before computers
. 1990: Iowa State University Press. 
33. 
Williams, J., 
Analog circuit design: art, science and personalities
. 1991: Newnes. 
34. 
Hubner, M., K. Paulsson, and J. Becker. 
Parallel and flexible multiprocessor system-
on-chip for adaptive automotive applications based on Xilinx microblaze soft-cores

IEEE. 
35. 
Nakamura, Y., et al. 
A fast hardware/software co-verification method for system-on-
a-chip by using a C/C++ simulator and FPGA emulator with shared register 
communication
. 2004: ACM. 
36. 
Schmitt, L.M., 
Theory of genetic algorithms.
Theoretical Computer Science, 2001. 
259(1-2): p. 1-61. 
37. 
Roser, M. and F. Moosmann. 
Classification of weather situations on single color 
images
. 2008: IEEE. 
38. 
Zheng, N.N., et al., 
Toward intelligent driver-assistance and safety warning system.
Intelligent systems, IEEE, 2004. 19(2): p. 8-11. 
39. 
Langheim, J., et al. 
CARSENSE-New environment sensing for advanced driver 
assistance systems
. 2001. 
40. 
Donecker, S.M., T.A. Lasky, and B. Ravani, 
A mechatronic sensing system for vehicle 
guidance and control.
Mechatronics, IEEE/ASME Transactions on, 2003. 8(4): p. 
500-510. 


 
121 
41. 
Kim, S.Y., et al., 
An Intelligent and Integrated Driver Assistance System for Increased 

Download 3,22 Mb.
1   ...   71   72   73   74   75   76   77   78   ...   81




Download 3,22 Mb.
Pdf ko'rish

Bosh sahifa
Aloqalar

    Bosh sahifa



Ultra fast cnn based Hardware Computing Platform Concepts for adas visual Sensors and Evolutionary Mobile Robots

Download 3,22 Mb.
Pdf ko'rish