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Mario V.

@mvigliar

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HW/FW/SW Engineer

$25 USD / Hour

Flag of

Italy (4:44 AM)

Joined on April 6, 2011

$25 USD / Hour

Doing Computer & Machine vision for industrial and scientific environments. New architectures and methodologies for embedded and low power systems. Able to architect, design and implement a complete digital system, from the HW components up to the basic firmware and software support. Fluent English speaking.

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Education

Università degli Studi di Salerno

2007 - 2010

3 years

PhD

Flag of

Italy

2007 - 2010

3 years

Università degli Studi di Salerno

2000 - 2005

5 years

2005

Flag of

Italy

2000 - 2005

5 years

Publications

Multiplierless coprocessor for difference of gaussian (dog) calculation

USPTO No. US 2013/0301950 A1

A hardware architecture is applied to the calculation of a Difference-of-Gaussian filter, which is typically employed in image processing algorithms. The architecture has a modular structure to easily allow the matching of the desired delay/area ratio as well as a high computational accuracy. A new solution is provided for the implementation of multiply-accumulators which allows a significant reduction of area with respect to the conventional architectures.

Hardware coprocessor for stripe-based interest point detection

USPTO No. US 2013/0301930 A1

A hardware coprocessor architecture calculates the Difference-of-Gaussian (DoG) pyramid of an input image and extracts from this the interest points to be used in several image detection algorithms. Advantages of the architecture include the possibility to process the image by stripes, namely by blocks having one dimension coincident with the input image width, in the absence of an input frame buffer and the possibility to avoid RAM memory. The coprocessor is suitable to be tightly coupled with raw image so

Modelling a fast BLAS level-1 inspired vectorized FPU for ARM devices

Circuits and Systems (MWSCAS), 2011 IEEE 54th International Midwest Symposium on

Modern collections of algorithms for DSP and multimedia often rely on linear algebra operators to perform massive numerical transformations on vectorized data. Embedded developers often experience the worst condition of having no FPU at all in their low-power systems, as many device producers consider FP-math as an expensive option in terms of gates and power consumption. Main aim of this work is to propose a lightweight structure, designed to be used in an ARM-based environment but easily retargetable to d

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US English - Level 1

US English

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