OneView
Working exclusively with real data creates significant challenges for machine learning model training. Synthetic data enables limitless machine learning model training, addressing the drawbacks and challenges of real data. Boost the performance of your geospatial analytics by creating the imagery you need. Customizable satellite, drone, and aerial imagery. Create scenarios, change object ratios, and adjust imaging parameters quickly and iteratively. Any rare objects or occurrences can be created. The resulting datasets are fully-annotated, error-free, and ready for training. The OneView simulation engine creates 3D worlds as the base for synthetic satellite and aerial images, layered with multiple randomization factors, filters, and variation parameters. The synthetic images replace real data for remote sensing systems in machine learning model training. They achieve superior interpretation results, especially in cases with limited coverage or poor-quality data.
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Amazon Rekognition
Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.
With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required.
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Google Cloud Vision AI
Derive insights from your images in the cloud or at the edge with AutoML Vision or use pre-trained Vision API models to detect emotion, understand text, and more. Google Cloud offers two computer vision products that use machine learning to help you understand your images with industry-leading prediction accuracy. Automate the training of your own custom machine learning models. Simply upload images and train custom image models with AutoML Vision’s easy-to-use graphical interface; optimize your models for accuracy, latency, and size; and export them to your application in the cloud, or to an array of devices at the edge. Google Cloud’s Vision API offers powerful pre-trained machine learning models through REST and RPC APIs. Assign labels to images and quickly classify them into millions of predefined categories. Detect objects and faces, read printed and handwritten text, and build valuable metadata into your image catalog.
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MAK ONE
A powerful and flexible Computer Generated Forces (CGF) platform to fill your synthetic environments with urban, battlefield, maritime, and airspace activity. VR-Engage lets users play the role of a first-person human character; a ground vehicle driver, gunner, or commander; or the pilot of a fixed-wing aircraft or helicopter. Game-like visual quality in a high-performance image generator. Designed by modeling & simulation experts for training and simulation projects. Physically accurate sensors, model the physics of light in any wavelength to represent electro-optical, night-vision, and infrared sensors. Applications that let you model, simulate, visualize, and participate in whole-earth multi-domain simulations. Multi-domain computer-generated forces. Multi-role virtual simulator. Image generator & battlefield visualization. EO, IR, and NVG imaging sensors. Synthetic aperture radar simulation.
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