Map-image matching using a multi-layer perceptron: the case of the road network

Automatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge

“…The information derived from maps gives data on the location of the objects to be found on the image, allowing the user to reduce the search space and minimize false alarms. Fiset et al (1998Fiset et al ( , 2003 and Bentabet et al (2003) provide interesting examples of map-guided methods.…”

Towards an operational system for automated updating of road databases by integration of imagery and geodata

“…The new roads, which are not in the existing road database, are extracted by a simple tracking algorithm after seed point detection. A similar approach is presented in Fiset et al (1998) for the correction and updating of road maps from georeferenced aerial images. They develop methods to match road intersections and road segments.…”

Automatic Extraction of Water Bodies from Landsat Imagery Using Perceptron Model

“…Similarly Gopal and Woodcock [52], Erbek et al [53], and Petra et al (2014) also employed MLP for pattern recognition and change detection studies. Similarly, MLP was used by Fiset et al [54] for image matching;Özkan and Erbek [55], Oliveira et al [56], and Fierens and Rosin [57] for classification and feature extraction from satellite images; Kotsiantis [58], Freund and Schapire [59], Canargo and Yoneyama [60], and Pal and Mitra [61] for Hyperspectral data classification. With respect to forestry, Vehtari and Lampinen [62] used MLP to identify tree trunks in digital images and Boschetti et al [63] for image fusion of hyperspectral data with pan data to extract vegetation under storey information.…”