Engineering C
Resume:
Chun-Chieh Yang, Ph.D.
Environmental Microbial and Food Safety Laboratory
Building 303, BARC-East, Powder Mill Road
Beltsville, MD 20705-2350
Email: ****-*****.****@***.****.***
Tel: 301-***-**** extension 232
EXPERTISE
Engineering
o Automation
o System management, integration, and control
o Food safety and defense
o Online food inspection
o Precision farming
o Water management
o Agricultural machinery
o Geographic information system
Computer modeling
o Artificial neural network
o Fuzzy logic
o Decision tree
o Multivariate adaptive regression splines
o Other data mining
Machine vision
o Image processing
o Image recognition, classification, and differentiation
o Line scan
o Online imaging
o Image spectrograph
Remote sensing
o Hyperspectral imaging
o Multispectral imaging
Computer programming
o MATLAB
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o LabVIEW
o Fortran
oC
PROFESSIONAL EXPERIENCE
2003 present: Agricultural Engineer/Research Associate, Environmental Microbial and
Food Safety Laboratory (formerly the Food Safety Laboratory until 2008), Agricultural
Research Service, United States Department of Agriculture.
o Accomplishments:
1. Developed an online high speed line-scan Raman imaging system for safety
inspection of fresh produce.
2. Commercialized an automated poultry carcass inspection system for Stork Food
and Dairy Systems, Inc.
2003 2008: Visiting Scientist, Food Safety Laboratory (formerly the Instrumentation
and Sensing Laboratory until 2007), Agricultural Research Service, United States
Department of Agriculture. Joint position as a Postdoctoral Scholar, Department of
Biosystems and Agricultural Engineering, University of Kentucky.
o Accomplishments:
1. Developed an online high speed line-scan imaging system for safety inspection of
poultry.
2. Commercialized an automated poultry carcass inspection system for Stork Food
and Dairy Systems, Inc.
3. Developed hyperspectral / multispectral image processing techniques for food
safety inspection of chicken carcasses.
4. Integrated artificial intelligence algorithms (based on neural networks, decision
trees, and fuzzy logic) into a machine vision system to implement image
processing techniques for an automated food safety inspection system on chicken
processing lines.
5. Analyzed hyperspectral data and determined essential multispectral image
features by which automated differentiation of wholesome and unwholesome
chickens could be performed.
6. Analyzed visible/near-infrared reflectance spectroscopy data for chicken meat and
developed neural network classification models to differentiate wholesome and
unwholesome chickens.
7. Assisted in testing and determination of operation parameters for the development
of a hyperspectral line-scan fluorescence imaging system for online safety
inspection of apples.
2004 2005: Artificial Neural Network Model for the Prediction of Nitrate
Concentrations in the Phreatic Aquifer of Esposende and Vila do Conde, project ref.
POCTI/MGS/47182/2002, the Science and Technology Foundation of the Portuguese
Science and Superior Education Ministry, Portugal.
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2001: Water Consumption Modeling in Northern China, Canadian International
Development Agency (CIDA) 3x3 Project, involving four Canadian universities (McGill
University, University of Toronto, University of British Columbia and University of
Montreal) and three Chinese universities (Beijing University, Chinghua University and
Nankai University), funded by Canadian International Development Agency (CIDA),
Canada.
2001: Efficient Planning of Montreal Urban Forests by Means of a Decision Making
Computerized System Project, Canada.
2000 2002: Postdoctoral Fellow, Department of Agricultural and Biosystems
Engineering, McGill University.
o Accomplishments:
1. Successfully adapted remote sensing methods of hyperspectral imaging to
develop hyperspectral imaging methodology and analysis techniques for weed
detection in precision agriculture.
2. Developed computer models based on artificial intelligence methods (neural
networks, decision trees, fuzzy logic) for weed differentiation from crops in
precision agriculture.
3. Integrated hyperspectral imaging methodology and analysis techniques with
computer models to successfully develop a complete weed management system
suitable for site-specific adaptation.
4. Developed computer models using artificial intelligence based on neural networks
for subsurface drainage/subirrigation water management systems.
5. Developed computer models using neural networks, decision trees, fuzzy logic,
and multivariate adaptive regression spline for higher efficiency in agrochemical
management.
6. Provided technical expertise as part of an international team of university
researchers conducting government-sponsored development of a geographic
information system to improve water resource management in urban areas.
Guided data collection and computer modeling used in GIS development.
7. Collaborated in project proposals successfully submitted for various grant
applications.
2000: Guest Speaker, Soil and Water Quality Management, Department of Natural
Resource Sciences, McGill University.
2000: Instructor, Structured Computer Programming, Department of Agricultural and
Biosystems Engineering, McGill University.
1997 1998: Teaching Assistant, Geographic Information System for Biosystems
Management, Department of Agricultural and Biosystems Engineering, McGill
University.
1996 1998: Teaching Assistant, Structured Computer Programming, Department of
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Agricultural and Biosystems Engineering, McGill University.
EDUCATION
Ph.D. 1995 2000. Department of Agricultural and Biosystems Engineering (was
renamed Department of Bioresource Engineering), McGill University, Canada.
M.Sc. 1993 1995. Department of Agricultural and Biosystems Engineering (was
renamed Department of Bioresource Engineering), McGill University, Canada.
B.Sc. 1986 1990. Department of Agricultural Machinery Engineering (was renamed
Department of Bio-Industrial Mechatronics Engineering), National Taiwan University,
Taiwan, R.O.C.
PROFESSIONAL ORGANIZATION MEMBERSHIP AND ACTIVITIES
Member of the American Society of Agricultural and Biological Engineers (ASABE).
1995 present
o Committee Member of ASABE Information and Electrical Technologies Division,
IET-312 Machine Vision. 2004 present
o Chair, ASABE Information and Electrical Technologies Division, IET-312 Machine
Vision. 2008 2009
o Vice Chair, ASABE Information and Electrical Technologies Division, IET-312
Machine Vision. 2007 2008
o Secretary, ASABE Information and Electrical Technologies Division, IET-312
Machine Vision. 2006 2007
AWARDS AND HONORS
Recognition for the "Electronics in Agriculture" Top-15 Achievement as part of "100
Years of Innovation" for ASABE Centennial Anniversary at the ASABE 2007
International Meeting in Minneapolis, MN, June 17-20, which highlighted the high-speed
poultry inspection system developed by the Instrumentation and Sensing Laboratory (was
renamed Food Safety Laboratory).
o International-wide competition
Honorable Mention, BARC Poster Day, Beltsville Agriculture Research Center,
Beltsville Area, USDA-ARS. 2006
o Area-wide competition
Extra Effort Award, USDA-ARS. 2004
o For the support provided to in-plant testing of the ISL commercial prototype
visible/near-infrared automated poultry inspection system at Tyson Foods chicken
processing facility in New Holland, PA
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Second Prize, BARC Poster Day, Beltsville Agriculture Research Center, Beltsville Area,
USDA-ARS. 2004
o Area-wide competition
Formation de chercheurs et l'aide la recherche (FCAR) (Recipient of Funds for the
training of researchers and the assistance with research), Quebec, Canada. 1997-1998
o Nationwide competition
Canadian Water Resources Association Graduate Scholarship, Canada. 1996
o Nationwide competition
PROFESSIONAL SERVICE
Associate Editor for the ASABE Publications, IET Division. 2007 - present
Manuscript reviewer for the following technical journals (listed alphabetically), 1999
present:
1. Biosystems Engineering
2. Canadian Water Resources Journal
3. Canadian Biosystems Engineering
4. Computers and Electronics in Agriculture
5. Hydrological Sciences Journal
6. Journal of the American Water Resources Association
7. Sensing and Instrumentation for Food Quality and Safety
8. Soil Science Society of America Journal
9. Transactions of the ASAE
10. Weed Research
11. Natural Resource Modeling
PATENT UNDER REVIEW
1. Chao, K., Y.-R. Chen, M. S. Kim, D. E. Chan and C.-C. Yang. 2007. Method and
System for Wholesomeness Inspection of Freshly Slaughtered Chickens on a Processing
Line.
REFEREED PUBLICATIONS
1. Yang, C.-C., K. Chao and M. S. Kim. 2009. Machine vision system for online inspection
of freshly slaughtered chickens. Sensing and Instrumentation for Food Quality and
Safety, 3(1): 70-80.
2. Chao, K., C.-C. Yang, M. S. Kim and D. E. Chan. 2008. High throughput spectral
imaging system for wholesomeness inspection of chicken. Applied Engineering in
Agriculture 24(4): 475-485.
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3. Chao, K., X. Nou, Y. Liu, M. S. Kim, D. E. Chan, C.-C. Yang, J. R. Patel and M.
Sharma. 2008. Detection of fecal/ingesta contaminants on poultry processing equipment
surfaces by visible and near-infrared reflectance spectroscopy. Applied Engineering in
Agriculture, 24(11): 49-55.
4. Kim, M. S., Y.-R. Chen, B. Cho, A. M. Lefcourt, K. Chao and C.-C. Yang. 2008. Online
hyperspectral line-scan fluorescence imaging for safety inspection of apples. Acta
Horticulturae, 768(1): 385-390.
5. Chao, K., C.-C. Yang, Y.-R. Chen, M. S. Kim and D. E. Chan. 2007. Hyperspectral-
multispectral line-scan imaging system for automated poultry carcass inspection
applications for food safety. Poultry Science, 86(11): 2450-2460.
6. Kim, M. S., Y.-R. Chen, B. K. Cho, K. Chao, C.-C. Yang, A. M. Lefcourt and D. E.
Chan. 2007. Hyperspectral reflectance and fluorescence line-scan imaging for online
defect and fecal contamination inspection of apples. Sensing and Instrumentation for
Food Quality and Safety, 1(3): 151-159.
7. Yang, C.-C., S. O. Prasher, S. Wang, S. H. Kim, C. S. Tan, C. Drury and R. M. Patel.
2007. Simulation of nitrate-n pollution in southern Ontario with DRAINMOD-N.
Agricultural Water Management, 87(3): 299-306.
8. Chao, K., C.-C. Yang, Y.-R. Chen, M. S. Kim and D. E. Chan. 2007. Fast line-scan
imaging system for broiler carcass inspection. Sensing and Instrumentation for Food
Quality and Safety, 1(2): 62-71.
9. Chao, K., Y.-R. Chen, F. Ding, C.-C. Yang and D.E. Chan. 2007. Development of two-
band color-mixing technique for identification of broiler carcass conditions. Journal of
Food Engineering, 80(1): 276-283.
10. Wang, S., S. O. Prasher, R. M. Patel, C.-C. Yang, S. H. Kim, A. Madani, P. M.
Macdonald and S. D. Robertson. 2006. Fate and transport of nitrogen compounds in a
cold region soil using DRAINMOD. Computers and Electronics in Agriculture, 53(2):
113-121.
11. Yang, C.-C., K. Chao, Y.-R. Chen, M. S. Kim and D. E. Chan. 2006. Development of
Fuzzy Logic-based Differentiation Algorithm and Fast Line-Scan Imaging System for
Chicken Inspection. Biosystems Engineering, 95(4): 483-496.
12. Liu, Y., K. Chao, Y.-R. Chen, M. S. Kim, X. Nou, D. E. Chan and C.-C. Yang. 2006.
Determination of key wavelengths in the detection of feces / ingesta contaminants for
sanitation verification at slaughter plants from visible and near infrared spectroscopy.
Journal of Near Infrared Spectroscopy, 14(5): 325-331.
13. Yang, C.-C., K. Chao, Y. R. Chen, M. S. Kim and H. L. Early. 2006. Simple region of
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interest analysis for systemically diseased chicken identification using multispectral
imaging. Transactions of the ASAE, 49(1): 245-257.
14. Yang, C.-C., K. Chao, Y. R. Chen and H. L. Early. 2005. Systemically diseased chicken
identification using multispectral images and region of interest analysis. Computers and
Electronics in Agriculture, 49(2): 255-271.
15. Yang, C.-C., K. Chao and Y. R. Chen. 2005. Development of multispectral imaging
processing algorithms for identification of wholesome, septicemia, and inflammatory
process chickens. Journal of Food Engineering, 69(2): 225-234.
16. Yang, C.-C., S. O. Prasher, R. Lacroix and S. H. Kim. 2004. Application of multivariate
adaptive regression splines (MARS) to simulate soil temperature. Transactions of the
ASAE, 47(3): 881-887.
17. Yang, C.-C., S. O. Prasher and P. K. Goel. 2004. Differentiation of crop and weeds by
decision-tree analysis of multi-spectral data. Transactions of the ASAE, 47(3): 873-879.
18. Yang, C.-C., S. O. Prasher, R. Lacroix and S. H. Kim. 2003. A multivariate adaptive
regression spines model for simulation of pesticide transport in soils. Biosystems
Engineering, 86(1): 9-15.
19. Yang, C.-C., S. O. Prasher, P. Enright, C. Madramootoo, M. Burgess, P. K. Goel and I.
Callum. 2003. Application of decision tree technology for image classification using
remote sensing data. Agricultural Systems, 76(3): 1101-1117.
20. Yang, C.-C., S. O. Prasher, J.-A. Landry and H. S. Ramaswamy. 2003. Development of a
herbicide application map using artificial neural networks and fuzzy logic. Agricultural
Systems, 76(2): 561-574.
21. Yang, C.-C., S. O. Prasher and J.-A. Landry. 2003. Development of an image processing
system and a fuzzy controller for site-specific herbicide applications. Precision
Agriculture, 4(1): 5-18.
22. Yang, C.-C., S. O. Prasher and J.-A. Landry. 2002. Weed recognition in corn fields using
back-propagation neural network models. Canadian Biosystems Engineering, 44:715-
722.
23. Yang, C.-C., S. O. Prasher, J. Whalen and P. K. Goel. 2002. Use of hyperspectral
imagery for identification of different fertilization methods with decision tree technology.
Biosystems Engineering, 83(3): 291-298.
24. Yang, C.-C., S. O. Prasher, J.-A. Landry and H. S. Ramaswamy. 2002. Development of
neural networks for weed recognition in corn fields. Transactions of the ASAE, 45(3):
859-864.
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25. Yang, C.-C., S. O. Prasher, J.-A. Landry and R. Kok. 2002. The development of image
processing and weed localization algorithms for precision farming. Biosystems
Engineering, 81(2): 137-146.
26. Yang, C.-C., S. O. Prasher, J.-A. Landry, J. Perret and H. S. Ramaswamy. 2000.
Recognition of weeds with image processing and their use with fuzzy logic for precision
farming. Canadian Agricultural Engineering, 42(4): 195-200.
27. Yang, C.-C., S. O. Prasher, J.-A. Landry, H. S. Ramaswamy and A. DiTommaso. 2000.
Application of artificial neural networks in image recognition and classification of crop
and weeds. Canadian Agricultural Engineering, 42(3): 147-152.
28. Yang, C.-C., C. S. Tan and S. O. Prasher. 2000. Artificial neural networks for subsurface
drainage and subirrigation systems in Ontario, Canada. Journal of the American Water
Resources Association, 36(3): 609-618.
29. Yang, C.-C., S. O. Prasher and C. S. Tan. 1999. An artificial neural network model for
water table management systems. Canadian Water Resources Journal, 24(1): 25-33.
30. Yang, C.-C., R. Lacroix, and S. O. Prasher. 1998. The use of back-propagation neural
networks for the simulation and analyses of time-series data in subsurface drainage
systems. Transactions of the ASAE, 41(4): 1181-1187.
31. Yang, C.-C., S. O. Prasher, R. Lacroix and A. Madani. 1997. Application of Artificial
neural networks in subsurface drainage system design. Canadian Water Resources
Journal, 22(1): 1-12.
32. Yang, C.-C., S. O. Prasher, R. Lacroix, S. Sreekanth, A. Madani and L. Masse. 1997.
Artificial neural network model for subsurface-drained farmlands. Journal of Irrigation
and Drainage Engineering, 123(4): 285-292.
33. Yang, C.-C., S. O. Prasher and G. R. Mehuys. 1997. An artificial neural network to
estimate soil temperature. Canadian Journal of Soil Science, 77(3): 421-429.
34. Yang, C.-C., S. O. Prasher, G. R. Mehuys and N. K. Patni. 1997. Application of artificial
neural networks for simulation of soil temperature. Transactions of the ASAE, 40(3): 649-
656.
35. Yang, C.-C., S. O. Prasher, S. Sreekanth, N. K. Patni and L. Masse. 1997. An artificial
neural network model for simulating pesticide concentrations in soil. Transactions of the
ASAE, 40(5): 1285-1294.
36. Sreekanth, S., S. O. Prasher and C.-C. Yang. 1997. Importance of choice of input
parameters in artificial neural network simulation of water-table depths. Canadian Water
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Resource Journal, 22(2): 111-124.
37. Yang, C.-C., S. O. Prasher and R. Lacroix. 1996. Applications of artificial neural
networks to simulate water-table depths under subirrigation. Canadian Water Resources
Journal, 21(1): 27-44.
38. Yang, C.-C., S. O. Prasher and R. Lacroix. 1996. Applications of artificial neural
networks to land drainage engineering. Transactions of the ASAE, 39(2): 525-533.
REFEREED PUBLICATIONS UNDER REVIEW
1. Yang, C.-C., D. E. Chan, K. Chao, Y.-R. Chen and M. S. Kim. 2007. Development and
in-plant testing of line-scan machine vision system for online poultry carcass inspection.
The Journal of Electronic Imaging.
CONFERENCE PROCEEDINGS AND TECHNICAL REPORTS
1. Yang, C.-C., K. Chao, M. S. Kim, D. E. Chan and Y. R. Chen. 2008. Multispectral
imaging system and differentiation algorithm for online inspection of poultry carcasses.
The American Society of Agricultural and Biological Engineers (ASABE), 2008
international meeting, paper no. 08-3925.
2. Yang, C.-C., K. Chao, M. S. Kim, D. E. Chan and Y. R. Chen. 2008. Online machine
vision system for inspection of poultry carcasses. The American Society of Agricultural
and Biological Engineers (ASABE), 2008 international meeting, paper no. 08-3926.
3. Chao, K., C.-C. Yang and M. S. Kim. 2008. High throughput spectral imaging system
for broiler carcass inspection. The American Society of Agricultural and Biological
Engineers (ASABE), 2008 international meeting, paper no. 08-3818.
4. Yang, C.-C., K. Chao, M. S. Kim and D. E. Chan. 2008. Machine vision system for
automatic online inspection of freshly slaughtered chickens. Food Processing Automation
Conference, Providence, RI, USA, June 28-29, 2008. The American Society of
Agricultural and Biological Engineers (ASABE).
5. Yang, C.-C., K. Chao and Y. R. Chen. 2007. Online application of machine vision
system for differentiation of wholesome and diseased poultry carcasses. The American
Society of Agricultural and Biological Engineers (ASABE), 2007 international meeting,
paper no. 07-3084.
6. Chen, Y.-R., B. K. Cho, C.-C. Yang, K. Chao and A.M. Lefcourt. 2007. Online line-scan
hyperspectral imaging for postharvest safety and quality inspection of apples. The
American Society of Agricultural and Biological Engineers (ASABE), 2007 international
meeting, paper no. 07-3026.
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7. Chao, K., C.-C. Yang, Y.-R. Chen, M. S. Kim and D. E. Chan. 2007. Fast-line scan
imaging system for chicken carcass inspection. The American Society of Agricultural and
Biological Engineers (ASABE), 2007 international meeting, paper no. 07-3032.
8. Yang, C.-C., D. E. Chan, K. Chao, Y. R. Chen and M. S. Kim. 2006. Development of
online line-scan imaging system for chicken inspection and differentiation. Optical
Sensors and Sensing Systems for natural Resources and Food Safety and Quality,
Proceedings of SPIE, Volume 6381, p. 63810Y-1-63810Y-10. OpticsEast 2006, Boston,
MA, USA, October 2-4, 2006. The International Society for Optical Engineering.
9. Chao, K., C.-C. Yang, Y. R. Chen, D. E. Chan and M. S. Kim. 2006. Poultry carcass
inspection by a fast line-scan imaging system: results from in-plant testing. Optical
Sensors and Sensing Systems for natural Resources and Food Safety and Quality,
Proceedings of SPIE, Volume 6381, p. 63810V-1-63810V-11. OpticsEast 2006, Boston,
MA, USA, October 2-4, 2006. The International Society for Optical Engineering.
10. Liu, Y., K. Chao, Y. R. Chen, M. S. Kim, X. Nou, D. E. Chan and C.-C. Yang. 2006.
Detection of fecal / ingesta contaminants at slaughter plants from a number of
characteristic visible and near infrared bands. Optical Sensors and Sensing Systems for
natural Resources and Food Safety and Quality, Proceedings of SPIE, Volume 6381, p.
63810U-1-63810U-9. OpticsEast 2006, Boston, MA, USA, October 2-4, 2006. The
International Society for Optical Engineering.
11. Kim, M. S., B.-K. Cho, C.-C. Yang, K. Chao, A. M. Lefcourt and Y. R. Chen. 2006.
Hyperspectral reflectance and fluorescence line-scan imaging system for online detection
of fecal contamination on apples. Optical Sensors and Sensing Systems for natural
Resources and Food Safety and Quality, Proceedings of SPIE, Volume 6381, p. 63810P-
1-63810P-8. OpticsEast 2006, Boston, MA, USA, October 2-4, 2006. The International
Society for Optical Engineering.
12. Yang, C.-C., K. Chao, Y.-R. Chen, M. S. Kim and D. E. Chan. 2006. Fuzzy logic-based
differentiation imaging system for systemically diseased chicken detection. The American
Society of Agricultural and Biological Engineers (ASABE), 2006 international meeting,
paper no. 06-3076.
13. Yang, C.-C., K. Chao, Y.-R. Chen, M. S. Kim, and D. E. Chan. 2006. Fast line-scan
imaging system using fuzzy logic-based differentiation algorithm for chicken inspection.
Institute of Food Technologists (IFT), 2006 annual meeting and food expo, presentation
no. 078E-09.
14. Yang, C.-C., K. Chao, Y. R. Chen, and M. S. Kim. 2006. Line-Scan Machine Vision
System for Online Poultry Carcass Inspection. April 26, 2004, BARC Poster Day.
Beltsville Agriculture Research Center, USDA-ARS.
15. Yang, C.-C., K. Chao, Y. R. Chen and M. S. Kim. 2005. Development of fast line
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scanning imaging algorithm for diseased chicken detection. Optical Sensors and Sensing
Systems for natural Resources and Food Safety and Quality, Proceedings of SPIE,
Volume 5996, p. 59960C-1-59960C-12. OpticsEast 2005, Boston, MA, USA, October 22-
23, 2005. The International Society for Optical Engineering.
16. Yang, C.-C., S. O. Prasher and J. Whalen. 2005. Application of hyperspectral imagery
and prediction algorithms to precision agriculture. The American Society of Agricultural
Engineers (ASAE), 2005 international meeting, paper no. 05-1062.
17. Yang, C.-C., K. Chao, Y. R. Chen and H. L. Early. 2005. Application of multispectral
imaging for wholesome and systemically diseased chickens. The American Society of
Agricultural Engineers (ASAE), 2005 international meeting, paper no. 05-3125.
18. Chao, K., Y. R. Chen, C.-C. Yang, and D. E. Chan. 2005. Characterizing spectra
variations for cleaning and sanitation issues in poultry processing plant The American
Society of Agricultural Engineers (ASAE), 2005 international meeting, paper no. 05-
3035.
19. Abreu, A. S., S. O. Prasher and C.-C. Yang. 2005. Development of REDENITRA, an
artificial neural network clone of RZWQM model, for the simulation of nitrate-N
leaching. The American Society of Agricultural Engineers (ASAE), 2005 international
meeting, paper no. 05-2112.
20. Abreu, A. S., S. O. Prasher and C.-C. Yang. 2005. REDENITRA, a backpropagation
artificial neural network (BANN) model, clone of RZWQM, that predicts the amount of
nitrate-N leaching in agricultural systems. EGU General Assembly 2005. Vienna, Austria.
21. Yang, C.-C., K. Chao, Y. R. Chen and H. L. Early. 2004. Systemically diseased chicken
identification using multispectral images and region of interest analysis. Nondestructive
Sensing for Food Safety, Quality, and Natural Resources, Proceedings of SPIE, Volume
5587, p. 121-132. OpticsEast 2004, Philadelphia, PA, USA, October 26-27, 2004. The
International Society for Optical Engineering.
22. Yang, C.-C., K. Chao and Y. R. Chen. 2004. Development of multispectral imaging
processing algorithms for Identification of Wholesome, Septicemic, and Inflammatory
Process Chickens. April 29, 2004, BARC Poster Day. Beltsville Agriculture Research
Center, USDA-ARS.
23. Yang, C.-C., K. Chao, Y. R. Chen and M. S. Kim. 2004. Application of multispectral
imaging for identification of wholesome and systemically diseased chicken. The
American Society of Agricultural Engineers (ASAE), 2004 international meeting, paper
no. 04-3034.
24. Yang, C.-C., K. Chao and Y. R. Chen. 2003. Development of multispectral imaging
processing algorithms for food safety inspection on poultry carcasses. The American
11
Society of Agricultural Engineers (ASAE), 2003 international meeting, paper no. 03-
3054.
25. Yang, C.-C., S. O. Prasher and J. Whalen. 2003. Neural network models for crop yield
classification using hyperspectral imagery. The American Society of Agricultural
Engineers (ASAE), 2003 international meeting, paper no. 03-1112.
26. Karimi, Y., S. O. Prasher, H. McNarin, R. B. Bonnell, P. Dutilleul, P. K. Goel, C.-C.
Yang and Y. Uno. 2003. Hyperspectral remote sensing for discriminating water and
nitrogen stresses in a corn field. The American Society of Agricultural Engineers (ASAE),
2003 international meeting, paper no. 03-1111.
27. Yang, C.-C. S. O. Prasher, S. Wang, S. H. Kim. C. S. Tan and C. Drury. 2002.
Simulation of nitrate-N pollution in southern Ontario with DRAINMOD-N. Northeast
Agricultural and Biological Engineering Conference (NABEC), 2002 annual meeting,
paper no. 02-028.
28. Yang, C.-C., S. O. Prasher and P. K. Goel. 2002. Differentiation of crop and weeds by
decision tree analysis of multi-spectral data. The American Society of Agricultural
Engineers (ASAE), 2002 international meeting, paper no. 02-1080.
29. Yang, C.-C., S. O. Prasher and J. Whalen. 2002. Prediction of yields for corn and
soybean with hyperspectral imagery. The American Society of Agricultural Engineers
(ASAE), 2002 international meeting, paper no. 02-3139.
30. Wang, S., S. O. Prasher, C.-C. Yang, S. H. Kim, A. Madani, P. M. MacDonald and S. D.
Robertson. 2002. Field validation of a mathematical model to estimate nitrate-nitrogen
pollution from subsurface drained farmlands. The American Society of Agricultural
Engineers (ASAE), 2002 international meeting, paper no. 02-2039.
31. Jutras, P., S. O. Prasher, C.-C. Yang and C. Hamel. 2002. Urban tree growth modeling
with artificial neural network. Proceedings of the 2002 International Joint Conference on
Neural Networks, IJCNN 02, Honolulu, Hawaii, USA, May 12-17, 2002: 1385-1389.
32. Yang, C.-C., S. O. Prasher, J. Whalen and P. K. Goel. 2001. Application of data mining
technology for hyperspectral imagery classification in agricultural fields. The American
Society of Agricultural Engineers (ASAE), 2001 international meeting, paper no. 01-
3116.
33. Goel, P. K., S. O. Prasher, R. M. Patel, J. A. Landry, A. A. Viau and C.-C. Yang. 2001.
Weed and nitrogen stress detection in corn using airborne hyperspectral remote sensing.
The American Society of Agricultural Engineers (ASAE), 2001 international meeting,
paper no. 01-1199.
34. Salehi, F., S. O. Prasher, S. Amin, A. Madani, S. J. Jebelli, H. S. Ramaswamy, C. Tan, C.
12
F. Drury and C.-C. Yang. 2001. Prediction of annual nitrate-N losses in drain outflows
with artificial neural networks. The American Society of Agricultural Engineers (ASAE),
2001 international meeting, paper no. 01-3064.
35. Yang, C.-C., S. O. Prasher, P. Enright, C. Madramootoo, M. Burgess, P. K. Goel and I.
Callum. 2001. Application of data mining technology for image classification using
remote sensing data. The Canadian Society of Agricultural Engineering (CSAE), 2001
annual meeting with the Northeast Agricultural and Biological Engineering Conference
(NABEC) and the Agricultural Institute of Canada (AIC), paper no. 01-611.
36. Yang, C.-C., S. O. Prasher, P. K. Goel and R. Patel. 2001. Application of data mining for
image classification in remote sensing. Journ e d information scientifique et technique en
g nie agroalimentaire, Saint-Hyacinthe, QC, Canada, March 21, 2001, 33-40.
37. Yang, C.-C., S. O. Prasher and J. A. Landry. 2000. Development of a weed management
system for precision farming. Northeast Agricultural and Biological Engineering
Conference (NABEC), 2000 annual meeting, paper no. 2031.
38. Yang, C.-C., S. O. Prasher and J. A. Landry. 2000. Applications of artificial neural
networks to plant recognition in the field. The American Society of Agricultural
Engineers (ASAE), 2000 international meeting, paper no. 00-3054.
39. Yang, C.-C., S. O. Prasher and J. A. Landry. 1999. Development of weed maps in corn
fields for precision farming. The American Society of Agricultural Engineers (ASAE),
1999 international meeting, paper no. 99-3044.
40. Yang, C.-C., S. O. Prasher and J. A. Landry. 1999. Weed recognition in precision
farming. The American Society of Agricultural Engineers (ASAE), 1999 international
meeting, paper no. 99-3115.
41. Yang, C.-C., S. O. Prasher and J. A. Landry. 1999. Use of artificial neural networks to
recognize weeds in a corn field. Journ e d information scientifique et technique en g nie
agroalimentaire, Saint-Hyacinthe, QC, Canada, March 3, 1999, 60-65.
42. Yang, C.-C., S. O. Prasher and J. A. Landry. 1998. Application of artificial neural
networks to image recognition in precision farming. The American Society of
Agricultural Engineers (ASAE), 1998 international meeting, paper no. 98-3039.
43. Yang, C.-C., S. O. Prasher and J. A. Landry. 1998. Application of image processing and
weed recognition in precision farming. Northeast Agricultural and Biological
Engineering Conference (NABEC), 1998 annual meeting, paper no. 9825.
44. Yang, C.-C., S. O. Prasher and C. S. Tan. 1998. An artificial neural network model for
water table management system. Drainage in the 21st Century: Food Production and the
Environment. Proceedings of the 7th Annual Drainage Symposium, Orlando, FL, USA,
13
March 8-10, 1998, p. 250-257.
45. Yang, C.-C., S. O. Prasher and J. A. Landry. 1997. Application of machine vision and
artificial neural networks in precision farming. The American Society of Agricultural
Engineers (ASAE), 1997 international meeting, paper no. 97-3107.
46. Yang, C.-C. and S. O. Prasher. 1997. Application of precision farming. CSAE
Conference Proceedings, volume A, Sherbrooke, QC, Canada, 1997. p. 71-80. Canadian
Society of Agricultural Engineering.
47. Yang, C.-C., S. O. Prasher and J. A. Landry. 1997. The use of information technologies
in precision farming. CSAE Conference Proceedings, volume A, Sherbrooke, QC,
Canada, 1997. p. 562-571. Canadian Society of Agricultural Engineering.
48. Yang, C.-C., S. O. Prasher and S. Sreekanth. 1996. An artificial neural network model
for pesticide fate and transport. The American Society of Agricultural Engineers (ASAE),
1996 international meeting, paper no. 96-2025.
49. Yang, C.-C., S. O. Prasher, R. Lacroix, S. Sreekanth, N. K. Patni and L. Masse. 1996. An
artificial neural network model for the simulation of water-table depths and drain
outflows. Proceedings of the 49th Annual Conference of the Canadian Water Resources
Association, Quebec City, June 26-28, 1996: 225-239.
50. Yang, C.-C., R. Lacroix, and S. O. Prasher. 1996. The use of back-propagation in neural
networks for the simulation and analyses of time-series data in subsurface drainage
systems. Proceedings of Computers in Agriculture, Cancun, Mexico, June 10-14, 1996:
941-949.
51. Yang, C.-C., S. O. Prasher and R. Lacroix. 1996. Application of artificial neural
networks in subsurface drainage system design. Proceedings of Computers in
Agriculture, Cancun, Mexico, June 10-14, 1996: 932-940.
52. Yang, C.-C., S. O. Prasher and R. Lacroix. 1995. Applications of artificial neural
networks to land drainage engineering. The Canadian Society of Agricultural
Engineering (CSAE), 1995 annual meeting, paper no. 95-610.
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