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Home » Archives for Michael A. Isnardi
Michael A. Isnardi

Michael A. Isnardi

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Publications

Computational sensing-low-power processing publications October 14, 2022

Low-Power In-Pixel Computing with Current-Modulated Switched Capacitors

David Zhang, Gooitzen van der Wal, Michael A. Isnardi, Michael Piacentino

We present a scalable in-pixel processing architecture that can reduce the data throughput by 10X and consume less than 30 mW per megapixel at the imager frontend.

Computational sensing-low-power processing publications March 18, 2022

Real-Time Hyper-Dimensional Reconfiguration at the Edge using Hardware Accelerators

Gooitzen van der Wal, David Zhang, Michael Piacentino, Michael A. Isnardi

In this paper we present Hyper-Dimensional Reconfigurable Analytics at the Tactical Edge using low-SWaP embedded hardware that can perform real-time reconfiguration at the edge leveraging non-MAC deep neural nets (DNN) combined with hyperdimensional (HD) computing accelerators.

Computational sensing-low-power processing publications April 1, 2021

Hyper-Dimensional Analytics of Video Action at the Tactical Edge

Michael A. Isnardi, David Zhang, Michael Piacentino, Gooitzen van der Wal

We review HyDRATE, a low-SWaP reconfigurable neural network architecture developed under the DARPA AIE HyDDENN (Hyper-Dimensional Data Enabled Neural Network) program. 

Information & computer science publications May 1, 2014

Forensic Prescreening System Using Coded Aperture Snapshot Spectral Imager

Michael A. Isnardi

We present a camera system for instantaneous, non-destructive capture of spectral signatures for forensic analysis. Our system detects highly probative samples in the forensic scene mixed by the multiple target objects by combining a coded aperture snapshot spectral imager with a multi-spectral detection algorithm.

Computer vision publications November 1, 2012

Vision Guided Compression on Low-Bit Rate Channels

Michael A. Isnardi

We introduce Vision Guided Compression (VGC), as a pre-processing technology that can be coupled with standards-based video coding, to provide FMV at low-bit rates.

Computational sensing-low-power processing publications June 1, 2012

Salience-Based Compression: Providing FMV Over Low-Bit Rate Channels

Michael A. Isnardi

We introduce Salience-Based Compression (SBC), a vision-guided pre-filtering technology, coupled with standards-based video coding.

Computer vision publications May 1, 2010

H.264 Format/Bitrate/Quality Tradeoff Study

Michael A. Isnardi, Bing-Bing Chai

Maximizing transmitted video quality at the highest resolution and highest frame rate is desirable,but multiple approaches can be employed to
maximize transmission quality for the video at a given bitrate.

Information & computer science publications May 1, 2006

Reduced Resolution Residual Coding for H.264-Based Compression System

Michael A. Isnardi

This paper describes a macroblock-based mixed resolution video encoding system. By reducing the spatial resolution of some macroblock residuals intelligently, our preliminary experiments show up to 20% improvement in video compression efficiency compared to H.264.

Information & computer science publications January 1, 2004

A Half D1 MPEG-4 Encoder on the BSP-15 DSP

Michael A. Isnardi

In this paper, we present the work on implementation of a half-D1interlaced MPEG-4 encoder with Equator Technology DSP chip, BSP-15.

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