Honggang Bu
Cited by
Cited by
Fabric defect detection based on multiple fractal features and support vector data description
H Bu, J Wang, X Huang
Engineering Applications of Artificial Intelligence 22 (2), 224-235, 2009
Active-optical sensors using red NDVI compared to red edge NDVI for prediction of corn grain yield in North Dakota, USA
LK Sharma, H Bu, A Denton, DW Franzen
Sensors 15 (11), 27832-27853, 2015
Detection of fabric defects by auto-regressive spectral analysis and support vector data description
HG Bu, XB Huang, J Wang, X Chen
Textile Research Journal 80 (7), 579-589, 2010
Use of corn height measured with an acoustic sensor improves yield estimation with ground based active optical sensors
LK Sharma, H Bu, DW Franzen, A Denton
Computers and Electronics in Agriculture 124, 254-262, 2016
Comparison of satellite imagery and ground‐based active optical sensors as yield predictors in sugar beet, spring wheat, corn, and sunflower
H Bu, LK Sharma, A Denton, DW Franzen
Agronomy Journal 109 (1), 299-308, 2017
Sugar beet yield and quality prediction at multiple harvest dates using active‐optical sensors
H Bu, LK Sharma, A Denton, DW Franzen
Agronomy Journal 108 (1), 273-284, 2016
Response of sunflower to nitrogen and phosphorus in North Dakota
E Schultz, T DeSutter, L Sharma, G Endres, R Ashley, H Bu, S Markell, ...
Agronomy Journal 110 (2), 685-695, 2018
Active Optical Sensor Algorithms for Corn Yield Prediction and a Corn Side-dress Nitrogen Rate Aid
DW Franzen, LK Sharma, H Bu
NDSU Circular SF1176-5, NDSU Extension Service Fargo, 2014
Evidence for the ability of active‐optical sensors to detect sulfur deficiency in corn
DW Franzen, LK Sharma, H Bu, A Denton
Agronomy Journal 108 (5), 2158-2162, 2016
Adaptive scheduling of smart home appliances using fuzzy goal programming
H Bu, K Nygard
The Sixth International Conference on Adaptive and Self-Adaptive Systems and …, 2014
Comparison of two ground-based active-optical sensors for in-season estimation of corn (Zea mays, L.) yield
LK Sharma, H Bu, DW Franzen
Journal of Plant Nutrition 39 (7), 957-966, 2016
Mechanical analysis on changing cross-sectional segment of fibre band in condensing zone in compact spinning
J Wang, JP Yang, HG Bu, T Fu, Q Xi, SP Zhou
The Journal of The Textile Institute 100 (5), 451-456, 2009
Fabric Defect Detection Using a Hybrid and Complementary Fractal Feature Vector and FCM-based Novelty Detector
J Zhou, J Wang, H Bu
Fibres and Textiles in Eastern Europe 25 (6), 46-52, 2017
A novel multiple fractal features extraction framework and its application to the detection of fabric defects
H Bu, X Huang
Journal of the Textile Institute 99 (5), 489-497, 2008
Yield and quality prediction using satellite passive imagery and ground-based active optical sensors in sugar beet, spring wheat, corn, and sunflower
H Bu
Master Thesis, Soil Science Department, North Dakota State University, 2014
A practical and robust way to the optimization of parameters in RBF kernel-based one-class classification support vector methods
H Bu, J Wang, X Huang
2009 Fifth International Conference on Natural Computation 1, 445-449, 2009
Sunflower type influences yield prediction using active optical sensors
DW Franzen, EC Schultz, TM DeSutter, LK Sharma, R Ashley, H Bu
Agronomy Journal 111 (2), 881-888, 2019
Mechanical analysis on constant cross-section segment of fiber band in condensing zone during compact spinning
J Yang, J Wang, H Bu, T Fu, Q Xi, S Zhou
Journal of the Textile Institute 103 (2), 117-123, 2012
North Dakota clay mineralogy impacts crop potassium nutrition and tillage systems
DW Franzen, H Bu
Feature Extraction Using Auto-Regression Spectral Analysis for Fabric Defect Detection
J Zhou, HG Bu, J Wang
Advanced Materials Research 175, 366-370, 2011
The system can't perform the operation now. Try again later.
Articles 1–20