Satellite Imagery
Satellite images allow Earthlings to view their planet from a broader perspective. However, interpreting the content of satellite imagery is a difficult task. The advancement in object detection techniques thanks to machine learning and computer vision paved the way for an entirely novel frontier of algorithms which when applied to satellite imagery provide insightful and transforming results. Modern machine learning techniques and subsequent artificial intelligence have significantly improved tasks like object counting, semantic segmentation, object detection and image classification. But before these machine learning algorithms can spring into action, they need to be trained on high-quality satellite imagery datasets. SunTec.AI provides training datasets with high quality and accurate annotations to enable satellites to detect and distinguish between a wide range of objects on Earth.
Training Data Services Offered by SunTec.AI for Satellite Imagery
Appropriate techniques of image and video annotation are used by experts at SunTec.AI, to generate training data for various objects like trees, roads, houses, buildings, rivers, seas, agricultural lands, urban and rural settlements etc.
- Aerial view mapping of urban and rural settlements
- Urban area layout
- Mapping of agricultural lands/fields
- Aerial monitoring
- Object localisation with 2D and Polygon techniques
- 2D aerial view imagery mapping
- Video annotation for moving objects
Why choose SunTec.AI?
At SunTec.AI, we ensure that our clients get the best-in-class training services while maintaining the highest accuracy level. Our experienced pool of experts has constantly achieved excellence in generating image and video annotations. Every training dataset produced at SunTec.AI goes through multiple stages of auditing and reviewing.
Expert annotators at SunTec.AI use best and popular techniques like bounding boxes, polygon and semantic segmentation for a top aerial view and aerial mapping. Our training data services have largely surpassed the expectations of our clients through our journey of over twenty years.
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We understand that the level of detail applied during data annotation directly impacts the overall accuracy and quality of the resultant AI algorithm’s predictions.
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