| 11. |
- Malki, Suleyman, et al.
(författare)
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A DT-CNN Data-Flow Implementation
- 2008
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Ingår i: 2008 11TH INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS. ; , s. 17-22
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Konferensbidrag (refereegranskat)abstract
- Digital implementations of Cellular Neural Networks are studied in terms of their communication requirements. Secure and reliable communication seems to imply close control, which degrades performance. We introduce a mechanism that removes the need for explicit local network control, taking the internal network communication out of the performance equation. This allows handling boundary conditions without introducing additional cells and facilitates multi-level implementations. A typical feature extraction task in hand vein recognition shows a 20x performance improvement for the Cellular Neural Network implementation.
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| 12. |
- Malki, Suleyman, et al.
(författare)
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An exploration of digital CNN implementations
- 2004
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Ingår i: Proceedings SSOCC.
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Konferensbidrag (refereegranskat)abstract
- Computationally hard problems, such as operations on n-dimensional maps, are in need of efficient solutions. Cellular Neural Networks have this promise. This paper explores digital realizations of such computational paradigms through the case of real-time image processing. It is shown that a behaviour-based spatial unrolling of the time-critical numerical convergence loop outperforms a classical function-based architecture. An FPGA implementation on Xilinx Virtex-II illustrates a 50 times higher throughput, bringing intelligent vision into reach.
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| 13. |
- Malki, Suleyman, et al.
(författare)
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Bit-Serial Approach Moves DT-CNN into Real-Time
- 2007
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Ingår i: Proceedings SSoCC2007.
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Konferensbidrag (refereegranskat)abstract
- The Cellular Neural Network provides an interesting template for non-linear signal processing. It is essentially based on 2nd-order (reaction / diffusion) differential equations. Harrer and Nossek have introduced the discrete-time equivalent that paves the ground for digital implementation. The interconnect requirements seem to have made it impossible to realistically implement this model. More than emulation is not possible for a network based on word-serial communication. In this paper, it is discussed that a bit-serial communication scheme brings a more realistic implementation. Furthermore, using also bit-serial techniques within each node permits to decrease the footprint and therefore makes a 2-level network for the direct implementation of reaction / diffusion mechanism possible.
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| 14. |
- Malki, Suleyman, et al.
(författare)
-
CNN image processing on a Xilinx Virtex-II 6000
- 2003
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Ingår i: Proceedings of the 16th European Conference on Circuit Theory and Design, ECCTD'03. - 8388309951 ; , s. 4-261
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Konferensbidrag (refereegranskat)abstract
- Image processing is one of the popular applications of Cellular Neural Networks. Macro enriched field-programmable gate-arrays can be used to realize such systems on silicon. The paper discusses a pipelined implementation that supports the handling of gray-level images at 180 to 240 Mpixels per second by exploiting the Virtex-II macros to spatially unroll the local feedback
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| 15. |
- Malki, Suleyman, et al.
(författare)
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Design Space Exploration for a DT-CNN
- 2008
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Ingår i: 2008 11TH INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS. ; , s. 69-74
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Konferensbidrag (refereegranskat)abstract
- The paper presents design considerations for a digital Cellular Neural Network. The architectural spectrum is categorized from a rich variety in nodal structural transformations and formulated by an exploration model. This model is then applied to study the influence of the memory band-gap. Experiments show the benefits of a tiled implementation, mixing spatial network parallelism with time-multiplexed nodes based on a local register stack.
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| 16. |
- Malki, Suleyman, et al.
(författare)
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Design Space Exploration for the integrated digital CNN Camera
- 2008
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Ingår i: 1st International Conference on Information Technology, 2008. - 9781424422449 ; , s. 107-110
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Konferensbidrag (refereegranskat)abstract
- The main thrust of CNN technology has been in analog implementations. Early attempts for digital implementations have a limited potential, confining the usage to for instance linear algorithms for B/W pictures. The paper looks into the prospects of successfully integrating the full CNN potential. This requires a carefully tuning of memory and network-on-chip bandwidth to the temporal/spatial aspects of the neural nodes. The paper introduces an exploration model and discusses architecture with application to streaming grey-scale images.
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| 17. |
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| 18. |
- Malki, Suleyman, et al.
(författare)
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Efficiency considerations for DT-CNN hardware
- 2007
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Ingår i: Proceedings MWSCAS NEWCAS. ; , s. 189-192
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Konferensbidrag (refereegranskat)abstract
- Cellular Neural Networks have become a popular paradigm for modeling nonlinear systems. First-hand implementations are in software on floating-point platforms for pure performance, while programmable analog circuitry has been tested for embedded low-power applications. The paper discusses gradual algorithmic and structural improvements that bring efficient digital hardware into consideration. This provides 32-bits floating-point accuracy on a block-scaled 12-bits fixed-point platform.
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| 19. |
- Malki, Suleyman, et al.
(författare)
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General introduction to ASIC design
- 2006
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Ingår i: Proceedings EWME. ; , s. 15-18
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Konferensbidrag (refereegranskat)abstract
- A basic training in VHDL with emphasis on FPGA implementation
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| 20. |
- Malki, Suleyman, et al.
(författare)
-
Hand Veins Feature Extraction using DT-CNNs
- 2007
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Ingår i: Proceedings of SPIE, the International Society for Optical Engineering. ; 6590
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Konferensbidrag (refereegranskat)abstract
- As the identification process is based on the unique patterns of the users, biometrics technologies are expected to provide highly secure authentication systems. The existing systems using fingerprints or retina patterns are, however, very vulnerable. One’s fingerprints are accessible as soon as the person touches a surface, while a high resolution camera easily captures the retina pattern. Thus, both patterns can easily be “stolen” and forged. Beside, technical considerations decrease the usability for these methods. Due to the direct contact with the finger, the sensor gets dirty, which decreases the authentication success ratio. Aligning the eye with a camera to capture the retina pattern gives uncomfortable feeling. On the other hand, vein patterns of either a palm of the hand or a single finger offer stable, unique and repeatable biometrics features. A fingerprint-based identification system using Cellular Neural Networks has already been proposed by Gao. His system covers all stages of a typical fingerprint verification procedure from Image Preprocessing to Feature Matching. This paper performs a critical review of the individual algorithmic steps. Notably, the operation of False Feature Elimination is applied only once instead of 3 times. Furthermore, the number of iterations is limited to 1 for all used templates. Hence, the computational need of the feedback contribution is removed. Consequently the computational effort is drastically reduced without a notable chance in quality. This allows a full integration of the detection mechanism. The system is prototyped on a Xilinx Virtex II Pro P30 FPGA.
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