Picterra, a Swiss AI-based SaaS platform allows users to interactively create a personalized AI detecting, localizing and counting any objects from satellite and aerial imagery. The company aims to democratize geospatial mapping, and its platform bridges the gap between Earth Observation (EO) imagery, cloud processing and geospatial insights by commoditizing Machine Learning technology. From precision agriculture to utilities and infrastructure, Picterra serves a wide variety of clients and provides customized services. Its main partners are geospatial and UAV mapping professionals looking to derive insights and actionable information for specific verticals based off large or heavy EO imagery set. The Picterra platform allows users to seamlessly integrate cutting edge machine learning technology into their existing workflow, so they can focus on their core business while achieving quick return on investment.
Along with the hardware and software sectors, the drone services market is the largest segment in the commercial drone industry with the strongest expansion. According to the market research report "Global Drone Service Market Analysis & Trends – Industry Forecast to 2025", the drone services market is estimated at USD 4.4 billion in 2019 and is projected to reach USD 63.6 billion by 2025, at a CAGR of 55.9% from 2019 to 2025. This is a huge opportunity for drone service providers. The key for capturing a share of this growing market is to offer turnkey business solutions beyond data capture, such as mapping, surveying and specialized geospatial analytics. With more and more business relying on location data to optimize their day-to-day operations and planning or gain first-hand market insights.
Picterra combines deep learning with human expertise to help you extract structured insights from Earth observation imagery. Our AI platform is designed to help you process a large volume of aerial or satellite images, detect objects and trends, and monitor change over any area or period of interest, enabling you to unlock key insights, all from your desk with just a few clicks. AI that works for you. We provide a powerful all-in-one AI feature-extraction, classification, and change detection solution. This makes your work easier by streamlining your geospatial analytic processes and producing higher quality results.
Here the human intelligence in charge is telling the AI model to have a look at these sections of the image. At this stage, only the human knows what is in the selected spots --sheep on a background in full shadow, sheep on the grass, and sheep on the bare ground. Defining areas where you know there are not examples of your object of interest helps the algorithm by enabling it to understand what you are NOT looking for looks like. The AI model will use these sections of your image as counterexamples. It is particularly helpful to draw the attention of the algorithm to areas where you have objects that look similar to your object of interest, but which are not that for which you are looking.
We have all heard of "automated" support features, but as artificial intelligence (AI) has continued to advance, the support landscape is shifting to focus on the possibility of "autonomous" support. What exactly is the difference? Here, Jens Trotzky, head of Artificial Intelligence Technology for SAP Support, discusses the role of AI in the development of autonomous support, and how SAP innovation is helping to make it a reality. A: Most customer support resources available today – even some of the most sophisticated – are considered automated in some capacity. In a nutshell, automated support is predictive technology that is pre-scripted by support engineers based on a fixed set of standards and defining factors.