Cao, D., & Nagle, M., & Lowell, C., & jolly, J., & Dhillon, R., & Morris, A. (2022, August), Cloud Computing Based Plant Classifiers and Their Real- Life Research Applications  Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--40890

\bibitem{asee_peer_40890}
  Cao, D., \& Nagle, M., \& Lowell, C., \& jolly, J., \& Dhillon, R., \& Morris, A. (2022, August), \emph{Cloud Computing Based Plant Classifiers and Their Real- Life Research Applications}
  Paper presented at 2022 ASEE Annual Conference \& Exposition, Minneapolis, MN.
  10.18260/1-2--40890

Deng Cao, Marcus Nagle, Cadance Lowell, joshua jolly, Rajveer Dhillon, and Augustus Morris.  "Cloud Computing Based Plant Classifiers and Their Real- Life Research Applications".  2022 ASEE Annual Conference & Exposition, Minneapolis, MN, 2022, August.  ASEE Conferences, 2022.  https://peer.asee.org/40890 Internet.  05 Feb, 2025

\bibitem{asee_peer_40890}
  Deng Cao, Marcus Nagle, Cadance Lowell, joshua jolly, Rajveer Dhillon, and Augustus Morris.
  "Cloud Computing Based Plant Classifiers and Their Real- Life Research Applications".
  \emph{2022 ASEE Annual Conference \& Exposition, Minneapolis, MN, 2022, August}.
  ASEE Conferences, 2022.
  https://peer.asee.org/40890 Internet.  05 Feb, 2025

@INPROCEEDINGS{asee_peer_40890
author = "Deng Cao, Marcus Nagle, Cadance Lowell, joshua jolly, Rajveer Dhillon, and Augustus Morris"
title = "Cloud Computing Based Plant Classifiers and Their Real- Life Research Applications"
booktitle = "2022 ASEE Annual Conference \& Exposition"
year = "2022"
month = "August"
address = "Minneapolis, MN"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/40890}
number = {10.18260/1-2--40890}
}

TY  - CPAPER
AB  - Funded by an 1890 Land Grant Evans-Allen research program and two USDA Capacity Building Grants, we have been introducing Artificial Intelligence and its modern applications to the undergraduate students in a minority institute for the past few years. This year, students are encouraged to use a cloud computing tool, i.e.Google Colab, to develop Deep Learning structures such as custom Convolutional Neural Networks. With Google’s free cloud services such as Linux hosted platform with GPU/TPU support and pre-installed libraries, undergraduate students with minimum Machine Learning background are able to learn, test, and customize neural networks in their browsers with their Google accounts. In particular, two undergraduate research tasks are discussed in detail. One is to distinguish sweet corn (Zea mays L. var. rugosa Bonaf.) in its vegetative stages from field weeds. The other is to classify 10 sweet potato (Ipomoea batatas) genotypes.  The students’ achievement using the Google Colab compared to using local machine are also discussed and reported in this work.
AU  - Deng Cao
AU  - Marcus Nagle
AU  - Cadance Lowell
AU  - joshua jolly
AU  - Rajveer Dhillon
AU  - Augustus Morris
CY  - Minneapolis, MN
DA  - 2022/08/23
PB  - ASEE Conferences
TI  - Cloud Computing Based Plant Classifiers and Their Real- Life Research Applications
UR  - https://peer.asee.org/40890
DO  - 10.18260/1-2--40890
ER  -