Cellular Neural Networks and Visual Computing

Chua, Leon O.; Roska, Tamás

doi:10.1017/cbo9780511754494

Cited by 524 publications

(315 citation statements)

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“…V Â W is the size of the CNN array (commonly a two-dimensional array) we presume that V is equal to W. The border cells must be treated differently (border conditions) according to [5] because they do not have the same number of neighbors as the inner cells. The output of a cell is generated by a nonlinear function (in this case the Chua's equation) as shown in Eq.…”

Section: Cellular Neural Networkmentioning

confidence: 99%

“…In the second approach, the control templates represent a predefined image-processing template (e.g., Sobel template or an averaging smoothing template), while the feedback templates are all zeros except the center element which represents the cell self-feedback. The goal of the second approach is to accelerate the related image-processing task (using its defined kernel as a CNN control template) via a CNN processor, which, due to its parallel paradigm, can operate much faster [5]. The latest mentioned predefined Kernels have been suggested in Refs.…”

Section: Using Support Vectors As Cnn Control Templatesmentioning

confidence: 99%

“…The latest mentioned predefined Kernels have been suggested in Refs. [3,5] for various pixel level image processing operations.…”

Section: Using Support Vectors As Cnn Control Templatesmentioning

confidence: 99%

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Real-time raindrop detection based on cellular neural networks for ADAS

Machot

Ali

Mosa

et al. 2016

J Real-Time Image Proc

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A core aspect of advanced driver assistance systems (ADAS) is to support the driver with information about the current environmental situation of the vehicle. Bad weather conditions such as rain might occlude regions of the windshield or a camera lens and therefore affect the visual perception. Hence, the automated detection of raindrops has a significant importance for video-based ADAS. The detection of raindrops is highly time critical since video pre-processing stages are required to improve the image quality and to provide their results in real-time. This paper presents an approach for real-time raindrops detection which is based on cellular neural networks (CNN) and support vector machines (SVM). The major idea is to prove the possibility of transforming the support vectors into CNN templates. The advantage of CNN is its ultra fast precessing on embedded platforms such as FPGAs and GPUs. The proposed approach is capable to detect raindrops that might negatively affect the vision of the driver. Different classification features were extracted to evaluate and compare the performance between the proposed approach and other approaches.

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Section: Cellular Neural Networkmentioning

confidence: 99%

Section: Using Support Vectors As Cnn Control Templatesmentioning

confidence: 99%

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Real-time raindrop detection based on cellular neural networks for ADAS

Machot

Ali

Mosa

et al. 2016

J Real-Time Image Proc

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“…A first electrical and on-chip candidate for SIMPL systems are Cellular Non-Linear Networks (CNNs) [22]. If successfully implemented, they would result in a technologically secure SIMPL system (see page 4).…”

Section: Introduction and General Ideamentioning

confidence: 99%

Towards Electrical, Integrated Implementations of SIMPL Systems

Rührmair¹,

Chen²,

Stutzmann

et al. 2010

Information Security Theory and Practices. Security and Privacy of Pervasive Systems and Smart Devices

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This paper discusses the practical implementation of a novel security tool termed SIMPL system, which was introduced in [1]. SIMPL systems can be regarded as a public key version of physical unclonable functions (PUFs). Like the latter, a SIMPL system S is physically unique and nonreproducible, and implements an individual function F S . In opposition to a PUF, however, a SIMPL system S possesses a publicly known numerical description, which allows its digital simulation and prediction. At the same time, any such simulation must work at a detectably lower speed than the real-time behavior of S. As argued in [1], SIMPL systems have certain practicality and security advantages in comparison to PUFs, certificates of authenticity, physically obfuscated keys, and also to standard mathematical cryptotechniques.In [1], definitions, protocols, and optical implementations of SIMPL systems were presented. This manuscript focuses on concrete electrical, integrated realizations of SIMPL systems, and proposes two potential candidates: SIMPL systems derived from special SRAM-architectures (socalled "skew designs" of SRAM cells), and implementations based on Cellular Non-Linear Networks (CNNs). IntroductionPhysical Unclonable Functions (PUFs) are a relatively young, emerging cryptographic primitive [2,3,4,5,6,7]. However, one potential downside of PUF-based protocols is that they usually require a previously shared piece of information (typically some challenge-response-pairs) that was established in a joint set-up phase between the communicants. Alternatively, an online connection to a trusted authority at the time of the protocol execution must be employed. In this particular structural aspect, PUFs are resemblant of classical private key systems.In this paper, we are concerned with an alternative security tool called SIMPL systems, which is a public key version of standard PUFs. SIMPL systems have been introduced in [1]. The acronym SIMPL stands for "SIMulation Possible, but Laborious", and hints at the critical security feature of these structures. A physical system S is called a SIMPL system if the following holds:1. It is possible for everyone to numerically simulate and, thus, to predict the physical behaviour of S with very high accuracy. The basis of the simulation is an individual description D(S) of S, and a generic simulation algorithm Sim, which are both publicly known.

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“…Conformal computing moves in that direction by exploring a computational medium assembled from "cells" that are much simpler than conventional instruction-processing 2 International Journal of Reconfigurable Computing nodes. Although the cells can be used to assemble conventional structures, our desire is to explore alternatives that are more similar to cellular automata [9], crystalline computing [10], cell matrices [11], BLOB computing [12], cellular neural nets [13], and the like. Therefore the cell designs emphasize simplicity (small multiplexors, 2-input logic units) and scalability (clock-less synchronization, multichip arrays) combined with features of cellular automata (regular structure, local communication) and FPGAs (reconfigurable function and initial state).…”

Section: Introductionmentioning

confidence: 99%

Design of a Reconfigurable Pulsed Quad-Cell for Cellular-Automata-Based Conformal Computing

Hoseini

Tan

You

et al. 2010

International Journal of Reconfigurable Computing

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This paper presents the design of a reconfigurable asynchronous computing element, called the pulsed quad-cell (PQ-cell), for constructing conformal computers. Conformal computers are systems with an exceptional ability to conform to the physical and computational needs of an application. PQ-cells, like cellular automata, are assembled into arrays, communicate with neighboring cells, and are collectively capable of general computation. They operate asynchronously to scale without the limitations of a global clock and to minimize power consumption. Cell operations are stimulated by pulses which travel on different wires to represent 0's and 1's. Cells are individually configured to perform logic, move and store information, and coordinate parallel activity. The PQcell design targets a 0.25 μm CMOS technology. Simulations show that a single cell consumes 15.6 pJ per operation when pulsed at 1.3 GHz. Examples of multicell structures include a 98 MHz ring oscillator and a 190 MHz pipeline.

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Cellular Neural Networks and Visual Computing

Cited by 524 publications

References 0 publications

Real-time raindrop detection based on cellular neural networks for ADAS

Real-time raindrop detection based on cellular neural networks for ADAS

Towards Electrical, Integrated Implementations of SIMPL Systems

Design of a Reconfigurable Pulsed Quad-Cell for Cellular-Automata-Based Conformal Computing

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