Results 141 to 150 of about 643,688 (353)
Comparative study of Land Use/Cover classification using Flickr photos, satellite imagery and Corine land cover database [PDF]
Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Volunteered ...
Estima, Jacinto +2 more
core +1 more source
This article develops a soft magnetic sensor array to extract 3D and distributional muscle deformations, which has highly consistent measurements in amphibious environments, robustness to hydraulic pressure, and about 200 ms faster response than an inertial measurement unit, achieving over 98% classification accuracy and below 3% phase estimation ...
Yuchao Liu +8 more
wiley +1 more source
Land Cover Classification Based on Airborne Lidar Point Cloud with Possibility Method and Multi-Classifier. [PDF]
Zhao D, Ji L, Yang F.
europepmc +1 more source
Fusing High-Spatial-Resolution Remotely Sensed Imagery and OpenStreetMap Data for Land Cover Classification Over Urban Areas [PDF]
Nianxue Luo +3 more
openalex +1 more source
Land cover classification combining Sentinel-1 and Landsat 8 imagery driven by Markov random field with amendment reliability factors [PDF]
Xiaofei Shi +3 more
openalex +1 more source
Land cover classification for Puget Sound, 1974-1979 [PDF]
Digital analysis of LANDSAT data for land cover classification projects in the Puget Sound region is surveyed. Two early rural and urban land use classifications and their application are described.
Eby, J. R.
core +1 more source
This review explores how shape‐changing structures—origami, bistable, and laminate structures—enable multifunctionality in soft robotics and metamaterials. Starting from structural design, it examines core principles, real‐world applications, and ongoing challenges.
Lingchen Kong, Yaoyao Fiona Zhao
wiley +1 more source
Deep learning for land cover and land use classification
Recent advances in sensor technologies have witnessed a vast amount of very fine spatial resolution (VFSR) remotely sensed imagery being collected on a daily basis. These VFSR images present fine spatial details that are spectrally and spatially complicated, thus posing huge challenges in automatic land cover (LC) and land use (LU) classification. Deep
Zhang, Ce, Atkinson, Peter
openaire +3 more sources
Land Cover Classification of UAV Remote Sensing Based on Transformer-CNN Hybrid Architecture. [PDF]
Lu T, Wan L, Qi S, Gao M.
europepmc +1 more source
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong +4 more
wiley +1 more source

