Using remote sensing to identify individual tree species in orchards: A review
A Ozdarici-Ok, AO Ok - Scientia Horticulturae, 2023 - Elsevier
Fruit trees are an essential subset of all tree species due to their high water and nutrient
content. They play a vital role in human nutrition and provide a significant economic boost …
content. They play a vital role in human nutrition and provide a significant economic boost …
An object-based convolutional neural network (OCNN) for urban land use classification
Urban land use information is essential for a variety of urban-related applications such as
urban planning and regional administration. The extraction of urban land use from very fine …
urban planning and regional administration. The extraction of urban land use from very fine …
A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification
The contextual-based convolutional neural network (CNN) with deep architecture and pixel-
based multilayer perceptron (MLP) with shallow structure are well-recognized neural …
based multilayer perceptron (MLP) with shallow structure are well-recognized neural …
TreeUNet: Adaptive tree convolutional neural networks for subdecimeter aerial image segmentation
Fine-grained semantic segmentation results are typically difficult to obtain for subdecimeter
aerial imagery segmentation as a result of complex remote sensing content and optical …
aerial imagery segmentation as a result of complex remote sensing content and optical …
Classification of land cover, forest, and tree species classes with ZiYuan-3 multispectral and stereo data
The global availability of high spatial resolution images makes mapping tree species
distribution possible for better management of forest resources. Previous research mainly …
distribution possible for better management of forest resources. Previous research mainly …
[HTML][HTML] Automated mapping of soybean and corn using phenology
For the two of the most important agricultural commodities, soybean and corn, remote
sensing plays a substantial role in delivering timely information on the crop area for …
sensing plays a substantial role in delivering timely information on the crop area for …
Feature learning based approach for weed classification using high resolution aerial images from a digital camera mounted on a UAV
The development of low-cost unmanned aerial vehicles (UAVs) and light weight imaging
sensors has resulted in significant interest in their use for remote sensing applications. While …
sensors has resulted in significant interest in their use for remote sensing applications. While …
On combining multiscale deep learning features for the classification of hyperspectral remote sensing imagery
In recent years, satellite imagery has greatly improved in both spatial and spectral
resolution. One of the major unsolved problems in highly developed remote sensing …
resolution. One of the major unsolved problems in highly developed remote sensing …
Densely based multi-scale and multi-modal fully convolutional networks for high-resolution remote-sensing image semantic segmentation
Automatic and accurate semantic segmentation from high-resolution remote-sensing images
plays an important role in the field of aerial images analysis. The task of dense semantic …
plays an important role in the field of aerial images analysis. The task of dense semantic …
A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas
In recent years, it has been widely agreed that spatial features derived from textural,
structural, and object-based methods are important information sources to complement …
structural, and object-based methods are important information sources to complement …