TY - JOUR
T1 - Columnar cactus recognition in aerial images using a deep learning approach
AU - López-Jiménez, Efren
AU - Vasquez-Gomez, Juan Irving
AU - Sanchez-Acevedo, Miguel Angel
AU - Herrera-Lozada, Juan Carlos
AU - Uriarte-Arcia, Abril Valeria
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/7
Y1 - 2019/7
N2 - Tehuacán-Cuicatlán Valley is a semi-arid zone in the south of Mexico. It was inscribed in the World Heritage List by the UNESCO in 2018. This unique area has wide biodiversity including several endemic plants. Unfortunately, human activity is constantly affecting the area. A way to preserve a protected area is to carry out autonomous surveillance of the area. A first step to reach this autonomy is to automatically detect and recognize elements in the area. In this work, we present a deep learning based approach for columnar cactus recognition, specifically, the Neobuxbaumia tetetzo species, endemic of the Valley. An image dataset was generated for this study by our research team, containing more than 10,000 image examples. The proposed approach uses this dataset to train a modified LeNet-5 Convolutional Neural Network. Experimental results have shown a high recognition accuracy, 0.95 for the validation set, validating the use of the approach for columnar cactus recognition.
AB - Tehuacán-Cuicatlán Valley is a semi-arid zone in the south of Mexico. It was inscribed in the World Heritage List by the UNESCO in 2018. This unique area has wide biodiversity including several endemic plants. Unfortunately, human activity is constantly affecting the area. A way to preserve a protected area is to carry out autonomous surveillance of the area. A first step to reach this autonomy is to automatically detect and recognize elements in the area. In this work, we present a deep learning based approach for columnar cactus recognition, specifically, the Neobuxbaumia tetetzo species, endemic of the Valley. An image dataset was generated for this study by our research team, containing more than 10,000 image examples. The proposed approach uses this dataset to train a modified LeNet-5 Convolutional Neural Network. Experimental results have shown a high recognition accuracy, 0.95 for the validation set, validating the use of the approach for columnar cactus recognition.
KW - Arid land
KW - Cactus
KW - Deep learning
KW - Drones
KW - Environmental conservation
UR - http://www.scopus.com/inward/record.url?scp=85066024258&partnerID=8YFLogxK
U2 - 10.1016/j.ecoinf.2019.05.005
DO - 10.1016/j.ecoinf.2019.05.005
M3 - Artículo
AN - SCOPUS:85066024258
SN - 1574-9541
VL - 52
SP - 131
EP - 138
JO - Ecological Informatics
JF - Ecological Informatics
ER -