[PDF][PDF] Kernel principal component analysis for the classification of hyperspectral remote sensing data over urban areas
Kernel principal component analysis (KPCA) is investigated for feature extraction from
hyperspectral remote sensing data. Features extracted using KPCA are classified using …
hyperspectral remote sensing data. Features extracted using KPCA are classified using …
Digital imaging for cultural heritage preservation
Paintings, frescoes, antique photographic prints, incunabula, old books, handwritten
documents, sculptures, ceramic fragments, and other ancient manufacts constitute the …
documents, sculptures, ceramic fragments, and other ancient manufacts constitute the …
Advanced directional mathematical morphology for the detection of the road network in very high resolution remote sensing images
Very high spatial resolution (VHR) images allow to feature man-made structures such as
roads and thus enable their accurate analysis. Geometrical characteristics can be extracted …
roads and thus enable their accurate analysis. Geometrical characteristics can be extracted …
Connected component-based technique for automatic extraction of road centerline in high resolution satellite images
C Sujatha, D Selvathi - EURASIP Journal on Image and Video Processing, 2015 - Springer
In remote sensing analysis, automatic extraction of road network from satellite or aerial
images can be a most needed approach for efficient road database creation, refinement …
images can be a most needed approach for efficient road database creation, refinement …
Road extraction techniques from remote sensing images: a review
D Patil, S Jadhav - … Technologies and Application: Proceedings of ICIDCA …, 2021 - Springer
Road detection from remotely sensed images is a fundamental task in the geographic
information system. On account of applications like urban management, traffic control, and …
information system. On account of applications like urban management, traffic control, and …
Semiautomatic road extraction framework based on shape features and LS-SVM from high-resolution images
Road network delineation from remote sensing imagery is useful in many applications
related to humans in present days as it provides meaningful information which is very helpful …
related to humans in present days as it provides meaningful information which is very helpful …
AM-UNet: Road Network Extraction from high-resolution Aerial Imagery Using Attention-Based Convolutional Neural Network
Roads are an essential element of various information systems such as geographic
information systems, transportation systems, etc. The main source of road information is …
information systems, transportation systems, etc. The main source of road information is …
RoadCompass: following rural roads with vision+ ladar using vanishing point tracking
C Rasmussen - Autonomous Robots, 2008 - Springer
We present a vision-and ladar-based approach to autonomous driving on rural and desert
roads that has been tested extensively in a closed-loop system. The vision component uses …
roads that has been tested extensively in a closed-loop system. The vision component uses …
Morphological path filtering at the region scale for efficient and robust road network extraction from satellite imagery
L Courtrai, S Lefèvre - Pattern Recognition Letters, 2016 - Elsevier
Roads are important elements in geographic information systems and remote sensing
applications. Their automatic extraction is challenging when only aerial or satellite images …
applications. Their automatic extraction is challenging when only aerial or satellite images …
Fourier-Deformable Convolution Network for Road Segmentation from Remote Sensing Images
H Liu, X Zhou, C Wang, S Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Road segmentation from remote sensing images is a challenging task in capturing weak,
long, and irregular road features due to the limited connectivity-preserving modeling …
long, and irregular road features due to the limited connectivity-preserving modeling …