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This paper introduces a topographic implementation of an SIMD array for B/W image processing of 48 times 48 processing elements on an FPGA. The computation is done with Boolean and shift operators. The connectivity among processing elements is set through the classical NEWS system. The array provides the functionality of a CNNUM. The paper shows examples of(More)
In this work we present a new proposal for image segmentation using deformable models, as an application of Discrete-Time Cellular Neural Networks (DTCNN) [1]. This approach is based on active contours (also called snakes) which evolve until reaching a final desired location. The contours are guided by both external information from the image under(More)
This paper addresses the extension of applications covered by binary CNN-based architectures. The work is focused on diffusion-like tasks on binary images, traditionally tackled by either large neighborhood or propagating templates on CNNUM architecture. The solution adopted here is to split large neighborhood into smaller templates (3/spl times/3) on a(More)
This paper introduces a methodology to reduce the number of coefficient circuits in a DTCNN cell without penalty at application level. Trade-offs like area-processing time, and some other figures of merit like accuracy and power dissipation are considered. It is shown that it is possible to obtain efficient implementations with a reduced number of(More)
The so-called split&shift (S&S) methodology has previously been introduced as an effective area saving technique for hardware implementation of cellular non-linear networks. This work provides the first experimental proof of such a methodology through a circuit implementation over an FPGA platform. Results of area, processing time and functionality(More)
This work aims at finding efficient configurations of coefficient circuits in a CNN hardware cell implementation based on the shape of the templates listed in the Cellular Wave Computing Library (CSW) and some applications/algorithms addressed in the CNN literature. The paper also touches briefly on possible hardware approaches to take advantage of the(More)
This paper introduces a systematic approach to enlarge the robustness in binary cellular nonlinear networks (CNN). In particular, the work is devoted to positive range CNN models with high gain nonlinearity and 1-bit of programmability. The robustness is increased by appropriately modifying the bias/threshold term. The CNN cell model and the robustness(More)
" Focal-plane dynamic texture segmentation by programmable binning and scale extraction, " in Single-exposure HDR technique based on tunable balance between local and global adaptation, " IEEE Trans. Bottom-up performance analysis of focal-plane mixed-signal hardware for Viola-Jones early vision tasks, " Int.plane sensing-processing: A power-efficient(More)
Computer-aided design (CAD) simulation tools offer the advantage of integrating both thermal and electrical simulations facilitating the study of new materials and structures. In this work, we demonstrate the possibility of using conventional electron devices simulation tools to study the thermoelectrical properties of non-typical semiconductor materials,(More)
Pests due to terrestrial mollusks cause serious damage, both economic and ecological, in various types of agricultural plantations. In this paper we develop a low cost capacitive sensor that wirelessly communicates with the base, to monitor the activity of land snails. Once implemented physically, it has been tested in a controlled miniplot with favorable(More)