S. Panigrahi

发表

A generalized regression neural network and its application for leaf wetness prediction to forecast plant disease

Y. Chtioui, S. Panigrahi, L. Francl, 1999 .

Biology and applications of olfactory sensing system: A review

S. Panigrahi, S. Sankaran, L. Khot, 2012 .

Independent component analysis-processed electronic nose data for predicting Salmonella typhimurium populations in contaminated beef

Suranjan Panigrahi, Curt Doetkott, Catherine M. Logue, 2008 .

Olfactory receptor based piezoelectric biosensors for detection of alcohols related to food safety applications

Sindhuja Sankaran, Suranjan Panigrahi, S. Panigrahi, 2011 .

Integrated electronic nose system for detection of Salmonella contamination in meat

Young K. Chang, J. Glower, Young Chang, 2008, 2008 IEEE Sensors Applications Symposium.

Simultaneous prediction of acetic acid/ethanol concentrations in their binary mixtures using metalloporphyrin based opto-electronic nose for meat safety applications

S. Panigrahi, J. Amamcharla, 2010 .

Prediction of Hepatic Steatosis (Fatty Liver) using Machine Learning

S. Panigrahi, R. Deo, 2019, ICCBB '19.

Evaluation of a commercial electronic nose system coupled with universal gas sensing chamber for sensing indicator compounds associated with meat safety

J. K. Amamcharla, Punyatoya Mohapatra, Suranjan Panigrahi, 2015, Journal of Food Measurement and Characterization.

Wavelet Transform: A Tool for Pattern Recognition of Olfactory Signal

S. Panigrahi, L. Khot, 2006 .

Evaluation of Surface Enhanced Raman Spectroscopy (SERS) for Detection of Acetone in the Context of Food Safety and Quality Application

S. Panigrahi, Punyatoya Mohapatra, 2012 .

Quantitative Determination of VOCs Using HS-SPME: A Comprehensive Reviewed Application for Meat Safety

S. Panigrahi, P. Bhattacharjee, 2007 .

About the National Nanotechnology Initiative about This Report about the Report Design Nanotechnology-enabled Sensing about the Workshop and This Report

M. Roukes, T. Thundat, H. Atwater, 2022 .

Neural-network-integrated electronic nose system for identification of spoiled beef

Suranjan Panigrahi, Catherine M. Logue, S. Balasubramanian, 2006 .

Solid-Phase Microextraction (SPME) Techniques for Quality Characterization of Food Products: A Review

Suranjan Panigrahi, Sundar Balasubramanian, S. Panigrahi, 2011 .

Investigation of Different Gas Sensor-Based Artificial Olfactory Systems for Screening Salmonella typhimurium Contamination in Beef

Suranjan Panigrahi, Catherine M. Logue, Julie S. Sherwood, 2012, Food and Bioprocess Technology.

Conjugate gradient and approximate Newton methods for an optimal probabilistic neural network for food color classification

Ronald Marsh, Suranjan Panigrahi, Younes Chtioui, 1998 .

Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques

Sudhanshu Sekhar Panda, Daniel P. Ames, Suranjan Panigrahi, 2010, Remote. Sens..

A comparative qualitative study of the profile of volatile organic compounds associated with Salmonella contamination of packaged aged and fresh beef by HS-SPME/GC-MS

S. Panigrahi, M. Marchello, P. Bhattacharjee, 2011, Journal of food science and technology.

Olfactory receptor-based polypeptide sensor for acetic acid VOC detection.

Sindhuja Sankaran, Suranjan Panigrahi, S. Panigrahi, 2012, Materials science & engineering. C, Materials for biological applications.

Odorant binding protein based biomimetic sensors for detection of alcohols associated with Salmonella contamination in packaged beef.

Sindhuja Sankaran, Suranjan Panigrahi, S. Panigrahi, 2011, Biosensors & bioelectronics.

A New Machine Learning-Based Complementary Approach for Screening of NAFLD (Hepatic Steatosis)

Edward A. Liechty, Suranjan Panigrahi, Ridhi Deo, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Evaluation of an artificial olfactory system for grain quality discrimination

Suranjan Panigrahi, S. Panigrahi, C. Wolf-Hall, 2007 .

Moisture prediction from simple micrometeorological data.

L J Francl, Y. Chtioui, S. Panigrahi, 1999, Phytopathology.

Fungicide Deposition Measurement by Spray Volume, Drop Size, and Sprayer System in Cereal Grains

S. Panigrahi, V. Hofman, H. Gu, 2008 .

Artificial Intelligence for Biology and Agriculture

Kuan Chong Ting, Suranjan Panigrahi, S. Panigrahi, 1998, Springer Netherlands.

Development and evaluation of chemoresistive polymer sensors for low concentration detection of volatile organic compounds related to food safety applications

Lav R. Khot, Suranjan Panigrahi, Partha Pratim Sengupta, 2010 .

Color computer vision for characterization of corn germplasm

Suranjan Panigrahi, S. Panigrahi, 1992 .

Neural networks-integrated metal oxide-based artificial olfactory system for meat spoilage identification

S. Balasubramanian, Suranjan Panigrahi, Catherine M. Logue, 2009 .

Residual soil nitrate prediction from imagery and non-imagery information using neural network technique

David W. Franzen, Suranjan Panigrahi, S. Panigrahi, 2011 .

Design and development of a metal oxide based electronic nose for spoilage classification of beef

Suranjan Panigrahi, Catherine M. Logue, M. J. Marchello, 2006 .

Performance of Polyvinylphenol-Carbon Black Composite as Ethanol Sensor for Food Safety Applications

Young K. Chang, S. Panigrahi, P. Sengupta, 2007 .

Artificial taste sensors: An overview

Punyatoya Mohapatra, Suranjan Panigrahi, S. Panigrahi, 2006 .

Artificial neural network models of wheat leaf wetness

Suranjan Panigrahi, S. Panigrahi, L. Francl, 1997 .

Evaluation of technique to overcome small dataset problems during neural-network based contamination classification of packaged beef using integrated olfactory sensor system

Lav R. Khot, Young K. Chang, Jacob S. Glower, 2012 .

Neural-Network-Based Classification of Meat: Evaluation of Techniques to Overcome Small Dataset Problems

Lav R. Khot, Suranjan Panigrahi, S. Woznica, 2008 .

Metalloporphyrin Based Opto-electronic Nose for Sensing Acetic Acid as an Indicator Compound of Meat Contamination

S. Panigrahi, J. Amamcharla, 2007 .

Development and evaluation of piezoelectric-polymer thin film sensors for low concentration detection of volatile organic compounds related to food safety applications

Lav R. Khot, Dongqing Lin, Suranjan Panigrahi, 2011 .

Temporal Analysis of VOC Profile of Packaged Meat during Spoilage

S. Panigrahi, L. Khot, P. Bhattacharjee, 2007 .

Nanoparticulate Zinc Oxide Chemoresistive Sensor for Volatile Acetic Acid Detection

S. Panigrahi, S. Sankaran, 2011 .

A System-Based Analysis and Approach for Water-Linked Health and Wellness in Low-Resource Setting

S. Panigrahi, 2018 .

IDENTIFICATION OF SALMONELLA-INOCULATED BEEF USING A PORTABLE ELECTRONIC NOSE SYSTEM

Suranjan Panigrahi, Catherine M. Logue, Julie S. Sherwood, 2005 .

Neural Network Optimisation of Remotely Sensed Maize Leaf Nitrogen with a Genetic Algorithm and Linear Programming using Five Performance Parameters

David W. Franzen, Suranjan Panigrahi, S. Panigrahi, 2006 .

Evaluations of fractal geometry and invariant moments for shape classification of corn germplasm

Manjit K. Misra, Stephen J. Willson, Suranjan Panigrahi, 1998 .

Performance Assessment of Machine Learning Based Models for Diabetes Prediction

Suranjan Panigrahi, Ridhi Deo, S. Panigrahi, 2019, 2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT).

Olfactory Sensing: Overview of the Biology, Mechanism and Applications for Food Safety

Sindhuja Sankaran, Suranjan Panigrahi, S. Panigrahi, 2006 .