I will apply deep learning in satellite imagery for segmentation and object detection

Unlock the full potential of your satellite imagery with Deep Learning!

I specialize in GeoAI and Deep Learning for remote sensing, providing accurate feature extraction, segmentation, and object detection from satellite and UAV imagery. My services are ideal for:

• Land cover segmentation: forests, water bodies, urban areas, vegetation
• Object detection: buildings, roads, vehicles, or any specific targets
• Change detection: comparing temporal imagery to monitor environmental or urban changes
• Feature extraction: terrain, hydrological, or geological features
• I use state-of-the-art Deep Learning models such as U-Net, Mask R-CNN, YOLO, and CNN-based architectures to deliver high-accuracy results.

Why choose me?

• Expertise in Deep Learning for geospatial data
• Strong background in GIS, Remote Sensing, UAV & LiDAR data
• Experience with Google Earth Engine, ArcGIS, QGIS, Pix4D, Python, and TensorFlow/PyTorch
• Deliverables include segmentation maps, object detection outputs, shapefiles, GIS layers, and detailed reports

Whether its environmental monitoring, urban planning, or hydrological studies, I turn complex satellite data into actionable, ready-to-use insights.