Boost precision agriculture with unmanned aerial vehicle remote sensing and edge intelligence: A survey
J Liu, J Xiang, Y Jin, R Liu, J Yan, L Wang - Remote Sensing, 2021 - mdpi.com
In recent years unmanned aerial vehicles (UAVs) have emerged as a popular and cost-
effective technology to capture high spatial and temporal resolution remote sensing (RS) …
effective technology to capture high spatial and temporal resolution remote sensing (RS) …
Deep-learning-based counting methods, datasets, and applications in agriculture: A review
The number of objects is considered an important factor in a variety of tasks in the
agricultural domain. Automated counting can improve farmers' decisions regarding yield …
agricultural domain. Automated counting can improve farmers' decisions regarding yield …
A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery
Visual inspection has been a common practice to determine the number of plants in
orchards, which is a labor-intensive and time-consuming task. Deep learning algorithms …
orchards, which is a labor-intensive and time-consuming task. Deep learning algorithms …
A high-precision detection method of hydroponic lettuce seedlings status based on improved Faster RCNN
In order to improve the efficiency and reduce high cost for seedlings sorting in the raising
process of hydroponic lettuce seedlings, we propose an automatic detection method for …
process of hydroponic lettuce seedlings, we propose an automatic detection method for …
A CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery
Accurately mapping croplands is an important prerequisite for precision farming since it
assists in field management, yield-prediction, and environmental management. Crops are …
assists in field management, yield-prediction, and environmental management. Crops are …
A near real-time deep learning approach for detecting rice phenology based on UAV images
Near real-time crop phenology detection is essential for crop management, estimation of
harvest time and yield estimation. Previous approaches to crop phenology detection have …
harvest time and yield estimation. Previous approaches to crop phenology detection have …
Mask R-CNN refitting strategy for plant counting and sizing in UAV imagery
M Machefer, F Lemarchand, V Bonnefond, A Hitchins… - Remote Sensing, 2020 - mdpi.com
This work introduces a method that combines remote sensing and deep learning into a
framework that is tailored for accurate, reliable and efficient counting and sizing of plants in …
framework that is tailored for accurate, reliable and efficient counting and sizing of plants in …
Rice seedling detection in UAV images using transfer learning and machine learning
To meet demand for agriculture products, researchers have recently focused on precision
agriculture to increase crop production with less input. Crop detection based on computer …
agriculture to increase crop production with less input. Crop detection based on computer …
Deep learning approaches and interventions for futuristic engineering in agriculture
With shrinking natural resources and the climate challenges, it is foreseen that there will be
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
an imminent stress in agricultural outputs. Deep learning provides immense possibilities in …
TasselNetV2+: A fast implementation for high-throughput plant counting from high-resolution RGB imagery
Plant counting runs through almost every stage of agricultural production from seed
breeding, germination, cultivation, fertilization, pollination to yield estimation, and harvesting …
breeding, germination, cultivation, fertilization, pollination to yield estimation, and harvesting …