Sapkota, B., Singh, V., Cope, D., Valasek, J. and Bagavathiannan, M. 2020. Mapping and estimating weeds in cotton using unmanned aerial systems-borne imagery. AgriEngineering, 2, 350-366. https://doi.org/10.3390/agriengineering2020024
Sapkota, B., Singh, V., Clark, N., Rajan, N. and Bagavathiannan, M. 2020. Detection of Italian ryegrass in wheat and prediction of competitive interactions using remote-sensing and machine-learning techniques. Remote Sensing, 12, 2977. https://doi.org/10.3390/rs12182977
Sapkota, B. B. and Liang, L. 2020. High-resolution mapping of Fraxinus spp. to slow down the Emerald Ash Borer infestation. Science of Remote Sensing, 1, 100004. https://doi.org/10.1016/j.srs.2020.100004
Sapkota, B. B. and Liang, L. 2018. A multistep approach to classifying full canopy and leafless trees in bottomland hardwoods using very high-resolution imagery. Journal of Sustainable Forestry, 37, 339-356. https://doi.org/10.1080/10549811.2017.1409637
Sapkota, B. B., Bhattarai, K. and Rimal, S. 2017. Study on internal timber demand-supply ratio in community forest users’ groups of the middle mountain region of Nepal. International Journal of Environment, 6, 42-55.
Sapkota, B.B., Hu, C. and Bagavathiannan, M.V., 2022. Evaluating cross-applicability of weed detection models across different crops in similar production environments. Frontiers in Plant Science, 13, p.837726.
Sapkota, B.B., Popescu, S., Rajan, N., Leon, R.G., Reberg-Horton, C., Mirsky, S. and Bagavathiannan, M.V., 2022. Use of synthetic images for training a deep learning model for weed detection and biomass estimation in cotton. Scientific Reports, 12(1), p.19580.
Hu, C., Sapkota, B. B., Thomasson, S. and Bagavathiannan, M. 2021. Influence of the image quality and light consistency on the performance of convolutional neural networks for weed mapping. Remote Sensing, 13, 2140. https://doi.org/10.3390/rs13112140
Kutugata, M., Hu, C., Sapkota, B. and Bagavathiannan, M. 2021. Seed rain potential in late-season weed escapes can be estimated using remote sensing. Weed Science, 1-21. https://doi.org/10.1017/wsc.2021.39
Liang, L., Runkle, B. R., Sapkota, B. B. and Reba, M. L. 2019. Automated mapping of rice fields using multi-year training sample normalization. International Journal of Remote Sensing, 40, 7252-7271. https://doi.org/10.1080/01431161.2019.1601286
Sapkota, B., Mirsky, S., Reberg-Horton, C. and Bagavathiannan, M. 2021. Exploring synthetic images and neural networks for weed detection and biomass estimation. Proceedings of American Society of Agronomy, Salt Lake City, UT, USA.
Sapkota, B., Hu, C., Mirsky, S., Reberg-Horton, C. and Bagavathiannan, M. 2021. Evaluating cross-applicability of weed detection models in different crop-weed environments. Proceedings of American Society of Agronomy, Salt Lake City, UT, USA.
Sapkota, B., Mirsky, S., and Bagavathiannan, M. 2020. Precise detection and biomass modeling of early season weeds in row crops using deep learning techniques. Proceedings of American Society of Agronomy (Virtual).
Sapkota, B., Howard, Z., Nolte, S., Rajan, N., Dotray, P., Morgan., G., and Bagavathiannan, M. 2020. Detection of herbicide drift injury and yield loss prediction in cotton using remote sensing and deep learning techniques. Proceedings of Agronomy Society of America (Virtual).
Sapkota, B., Singh, V., Mirsky, S., and Bagavathiannan, M. 2020. Advanced image analysis approaches for weed species segmentation in cotton. Proceedings of Weed Science Society of America, Maui, Hi, USA.
Sapkota, B., Singh, V., and Bagavathiannan M. 2019. Early prediction of the level of infestation and competitive interactions of Italian ryegrass in wheat using digital image analysis. Proceedings of American Society of Agronomy, San Antonio, TX, USA.
Sapkota, B., Singh, V., Cope, D., and Bagavathiannan, M. 2019. Classification of weeds in row crops using unmanned aerial systems. Proceedings of Weed Science Society of Agronomy, New Orleans, LA, USA.
Sapkota, B., Bataneih, M., and Liang, L. 2018. High-resolution mapping ash (Fraxinus spp.) - host of emerald ash borer in bottomland hardwoods. Proceedings of Arkansas Space Grant Consortium, Little Rock, AR, USA.