Dynamic Vision Sensor integration on FPGA-based CNN accelerators for high-speed visual classification

Deep-learning is a cutting edge theory that is being applied to many fields. For vision applications the Convolutional Neural Networks (CNN) are demanding significant accuracy for classification tasks. Numerous hardware accelerators have populated during the last years to improve CPU or GPU based solutions. This technology is commonly prototyped and tested over FPGAs before being considered for ASIC fabrication for mass production. The use of commercial typical cameras (30fps) limits the capabilities of these systems for high speed applications. The use of dynamic vision sensors (DVS) that emulate the behavior of a biological retina is taking an incremental importance to improve this applications due to its nature, where the information is represented by a continuous stream of spikes and the frames to be processed by the CNN are constructed collecting a fixed number of these spikes (called events). The faster an object is, the more events are produced by DVS, so the higher is the equivalent frame rate. Therefore, these DVS utilization allows to compute a frame at the maximum speed a CNN accelerator can offer. In this paper we present a VHDL/HLS description of a pipelined design for FPGA able to collect events from an Address-Event-Representation (AER) DVS retina to obtain a normalized histogram to be used by a particular CNN accelerator, called NullHop. VHDL is used to describe the circuit, and HLS for computation blocks, which are used to perform the normalization of a frame needed for the CNN. Results outperform previous implementations of frames collection and normalization using ARM processors running at 800MHz on a Zynq7100 in both latency and power consumption. A measured 67% speedup factor is presented for a Roshambo CNN real-time experiment running at 160fps peak rate.Comment: 7 page

LEVANTAMIENTO TOPOGRAFICO PARA DISEÑO DE SISTEMA DE AGUA POTABLE POR GRAVEDAD Y SANEAMIENTO AMBIENTAL, VALLE LOS CONDEGAS, MUNICIPIO EL CUA, EN EL PERÍODO 1RO.AL 31 DE MAYO DEL 2016

Este proyecto se trata de Levantamiento Topográfico en el valle Los Condegas Municipio El Cua, desarrollado como medio de pre-factibilidad producto de la necesidad sentida en la población antes descrita y manifestada a la municipalidad. La razón de este estudio es la preparación para la formulación de proyecto de Agua Potable y Saneamiento en el Valle Los Condegas. Para el cual se delimitó el área de incidencia desde el punto inicial o captación hasta el último beneficiario de la línea de cobertura. Además se presenta lista general de beneficiario con su ubicación geografía a lo largo de los 8485.60 ml de levantamiento general en toda su cubertur

Safety-Critical Java on a Java Processor

The safety-critical Java (SCJ) specification is developed within the Java Community Process under specification request number JSR 302. The specification is available as public draft, but details are still discussed by the expert group. In this stage of the specification we need prototype implementations of SCJ and first test applications that are written with SCJ, even when the specification is not finalized. The feedback from those prototype implementations is needed for final decisions. To help the SCJ expert group, a prototype implementation of SCJ on top of the Java optimized processor is developed and presented in this paper. This implementation raises issues in the SCJ specification and provides feedback to the expert group

The Glass House

A collaboration of Architects and Architectural Engineers to design a unique depiction of the 50x50 Glass House with Miesian Architectural appeal

The use of GeoGebra in Discrete Mathematics

In this paper we explain how to make use of the commands that are available in GeoGebra to deal with some realistic problems related to the field of Discrete Mathematics. We also expose how to define new tools that make possible the study of theoretical results in Graph theory

The use of GeoGebra in Discrete Mathematics

In this paper we explain how to make use of the commands that are available in GeoGebra to deal with some realistic problems related to the field of Discrete Mathematics. We also expose how to define new tools that make possible the study of theoretical results in Graph theory