Advances in Object and Activity Detection in Remote Sensing Imagery

• Beste egile batzuk: Ulhaq, Anwaar (Argitaratzailea), Gomes, Douglas Pinto Sampaio (Argitaratzailea)
• Formatua: Baliabide elektronikoa Liburu kapitulua
• Hizkuntza: ingelesa
• Argitaratua: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Gaiak: Technology: general issues; History of engineering & technology; multi-camera system; space alignment; UAV-assisted calibration; cross-view matching; spatiotemporal feature map; view-invariant description; air-to-ground synchronization; tidal flat water; YOLOv3; similarity algorithm for water extraction; arbitrary-oriented object detection in satellite optical imagery; adaptive dynamic refined single-stage transformer detector; feature pyramid transformer; dynamic feature refinement; synthetic aperture radar (SAR); ship detection; convolutional neural network (CNN); deep learning (DL); feature pyramid network (FPN); quad feature pyramid network (Quad-FPN); crowd estimation; 3D simulation; unmanned aerial vehicle; synthetic crowd data; invasive species; thermal imaging; habitat identification; deep learning; drone; multiview semantic vegetation index; urban forestry; green view index (GVI); semantic segmentation; urban vegetation; RGB vegetation index; n/a
• Sarrera elektronikoa: DOAB: download the publication; DOAB: description of the publication

The recent revolution in deep learning has enabled considerable development in the fields of object and activity detection. Visual object detection tries to find objects of target classes with precise localisation in an image and assign each object instance a corresponding class label. At the same t...