Michael Nigro — accepted AI-conference papers

2023

Digital Phenotype Representation by Statistical, Information Theory, Data-Driven Approach with Digital Health Data

Binh P. Nguyen, Michael Nigro, Alice Rueda, Venkat Bhat, Sridhar Krishnan

ICASSP 2023accepted

Digital phenotyping (DP) is a multidisciplinary field of science that quantifies the individual level phenotype through active and passive data. Although DP is a multidisciplinary field, there lacks a technical and a systematic approach to representing DP. This work proposes the development of digit…

Cited by 0 Source ↗Scholar ↗

2023

SARdBScene: Dataset and Resnet Baseline for Audio Scene Source Counting and Analysis

Michael Nigro, Sridhar Krishnan

ICASSP 2023accepted

This paper introduces a first of its kind dataset for audio scene analysis (ASA) and presents a baseline approach for audio source counting. SARdBScene is developed to promote research for audio source counting, as a relatively new ASA task, and present a comprehensive dataset that covers a variety…

Cited by 0 Source ↗Scholar ↗