1 |
Tang, L., L. Tian and B. Steward. 2000. Development of a low-cost machine vision system for selective sprayer. ASAE Paper No. 003064. ASAE.
|
2 |
Vrindts, E., J. De Baerdemaeker and H. Ramon. 2002. Weed detection using canopy reflection. Precision Agriculture, 3:63-80.
DOI
ScienceOn
|
3 |
Steward, B. L. and L. F. Tian. 1998. Real-time machine vision weed sensing. ASAE Paper No. 98-3033. ASAE.
|
4 |
El-Faki, M. S., N. Zhang and D. E. Peterson. 2000. Weed detection using color machine vision. Trans. of the ASAE. 43(6):1969-1978.
DOI
|
5 |
Wang, Ning, N. Zhang, D. E. Perterson and F. E. Dowell. 2000. Testing of a spectral-based weed sensor. ASAE Paper No. 003127. ASAE.
|
6 |
Suh, S. R., J. H. Sung and G. C. Chung. 2001. Comparison of nutrient deficient stress diagnoses of cucumber plant using non-destructive physiological instruments. Agric. and Biosystems Engineering. 2(1):1-6, KSAM.
과학기술학회마을
|
7 |
Borregaard, T., H. Nielsen, L. Norgaard and H. Have. 2000. Crop-weed discrimination by line imaging spectroscopy. J. agric. Engng Res. 75: 389-400.
DOI
ScienceOn
|
8 |
Cho, S. I., D. S. Lee and J. Y. Jeong. 2000. Weed detection by machine vision and artificial neural network. Proceedings of ICAME 2000. 2:270-278. KSAM.
과학기술학회마을
|
9 |
Woebbecke, D. M., G. E. Meyer, K. Von Bargen and D. A. Mortensen. 1995. Color indices for weed identification under various soil, residue, and lighting conditions. Trans. of the ASAE. 38(1):259-269.
DOI
|