An AI Data management and Inference platform for Computer Vision AI that takes holistic
approach to build, sustain and deliver to address needs of the business executives, domain
application users, Al Engineers, Al Researchers, Developers, Data Scientists & Annotators.
Use Skydnn to run and visualize computer vision
AI inferences along with visual quantification using
pre-trained ready-to-use AI models or custom models
Use Skydnn's key Distributed Asset Management foundation to manage large sets of satellite imagery and street photographs while preserving and accessing their respective spatial and temporal context to enable seamless integration with distributed computer vision AI pipelines and GIS systems/solutions
Use Skydnn Annotation workflow and tools for creating
annotations for various computer vision AI tasks
Use Skydnn Annotation workflow and tools for creating
annotations for various computer vision AI tasks
Anon flow
TEPPr flow
Progressive Web Apps for unstructured data management, annotations, Al assisted
annotation processing, visual quantification and feedback loop for 360 degree MLOps
Distributed data management for unstructured data for AI and geospatials.
Universal Al Annotation platform for spatial-temporal data for computer vision AI.
Computer Vision Al data with Raw annotations and Al Database for different use cases.
Progressive Web Apps for end-to-end Al enabled web apps, pipelines and workflows
Declarative AI API and SDK components for end to end Al pipeline and workflow.
Pre-trained Computer Vision AI models trained in-house and made accessbile to using Skydnn REST AI APIs.
AI empowering organisations to provider enhanced customer experience and improved efficiency
To extensively train autonomous driving perception models and complex use cases to suite autonomous requirements.
AI perception models trained on different resolutions on Satellite Imagery cater to address the increasing need of Urban Planing & Smart Cities for the AOI (Area of Interest).
To identify a variety of objects on Drone Imagery, Satellite Imagery, Street Imagery for management, maintenance, monitoring purposes.
During disasters/calamities Drones & High Resolution Satellite Imagery allow to assess ground reality. AI models trained extensively to assess damages and identify changes can help decision makers.
To identify a variety of objects on Drone Imagery, Satellite Imagery, Street Imagery for management, maintenance, monitoring purposes.
To identify by detection or classification on a variety of objects on Satellite Imagery, Street Imagery for environment and agriculture use cases.
Segmentation of Satellite Imagery or AOI (Area of Interest) into different distinctive Land, Road, and Geographical Feature categories.
Classification of Satellite Imagery tiles/chips or AOI (Area of Interest) into different types of Water bodies, Built-up area, Vegetation.
Road quality impacts travel time, vehicle maintenance & vehicle insurance cost. Assess quality of roads through AI for pot holes, cracks, speed bumps etc.
Objects geospatially tagged, detected & monitored using AI on large construction sites, outdoor infrastructure & utlities, road side big trees & indoor assets for large warehouses.
100s of different traffic sign type detection and categorisation to recognize for infrastructure management, on road autonomous vehicles.
AI models required to detect road edges, road boundaries, lane markings as polyline assist on road autonomous vehicles in navigation planning.
Perception of environment for motion planning and detection of junction, curb, traffic signs, lane obstacles, dividers, pedestrains for autonomous vehicles.
AI detects Road edges, road type, lane marking & type, speed breakers, pot holes, junctions, curb and dividers for effective path planning for autonomous vehicles.
Accelerate HD Mapping using AI assisted processing for different object categories essential for mapping and autonomous vehicles.
Detection and estimation of forest cover and vegetation losses during disaster.
AI models trained to detect Vehicles, Vehicle type, Pedestrian, Junction, curb and divider can assist autonomous vehicles to avoid collision by forewarining.
AI models trained to detect road sign, traffic sign detection, vacant parking spot helps to identify parking slots for the autonomous vehicles.
AI trained for infrastructure infiltration detects helipad, bridge, harbour, camp establishment, storage shed, shelter, gun area and construction site.
Military targets like gun areas, helipad, storage shed, shelter, camp establishment, bridge, harbour detection using AI on remote sensing data to empower decision makers with ground reality.
AI can assist detection on remote sensing data for ground forces covering gun area, storage shed, shelter, camp establishment and convoy movement.
AI models trained to detect forest land, trees, field parcels, live stocks, weeds, categorising regions covered in snow or ice, various types of water bodies.
Detection of field parcels, live stocks on high resolution satellite imagery.
Segmentation of soil, water, roads, vegetation for geoanalytical purpose.
Classification of Satellite Imagery tiles/chips or AOI (Area of Interest) into different types of land usage like residential, industrial.
Automate the scanning of large area using temporal satellite imagery to detect any temporal changes to assist timely decision by decision makers.
POI (Point Of Interest) detected indirectly through facade (front of building), shopping sigh board, text detection on the shopping sign board, brand detection.
Road sign boards detection and their categorisation helps to recognize road signboards.
Shops are specialised point of interest and text detection on shopping sighboard assists in text recognition automation.
Point of Interest text detection leads to POI detection and input for text recognition of the detected text for geospatial and mapping automation.
PII category detection and anonymization, GDPR compliance for Vehicle number plate masking, Face masking.
Vehicle number plate recognition includes detection of number plate and the vehicle number as editable text for parking management, toll booth automation on videos.
Approximate building height estimation from satellite imagery using computer vision accelerates infrastructure management and mapping.
Detect vehicles and identify different vehicle types useful for autonomous vehicles, parking management, toll booth monitoring.
Person detection or if a pedestrian detection on street or indoor imagery is useful for counting, monitoring purposes.
Detection of text on street sign boards, shopping board, signages in different Indic languages and English.
Text recognition in different Indic languages and English.
Classification of images containing single or multiple types of categories like images containing traffic signs. These set of AI models powers visual and semantic search.
Classification of objects belonging to a single category or a set of categories.
Detection of one or more objects of same or different types in the given image.
Categorizing each pixel in the image belonging to a single category generating a segmentation mask of the given object.
All objects identified have an individual instance segmentation mask.
Estimation of the depth of the objects from the given input 2D image by generating the depth map from the single image.
Convert black and white or grey images to colorized image that represents the semantic colors and tones of the input image.
Converting 2D points from images into 3D points without using depth information useful for vehicle intelligence, HD Mapping and geospatial analytics.
Tracking the multiple detected objects at the same time across the image sequences or video frames retaining their unique identities.
The sequence of images converted into 3D point cloud using photogrammetry or AI.
Estimate the flow using AI of all pixels in the image between two consecutive video frames is useful for understanding behavior and scene dynamics for varied applications.
Contact us to let us know what you are looking for. Our AI experts will help you on your AI journey.