See beyond a single case. (Former: RadiologyExplorer)
Contextflow applies state of the art machine learning and semantic analysis to big medical data and identifies clinically relevant structures in medical images. It allows radiologists to mark a region of interest containing a pathological appearance in an medical image (e.g. CT or MRI) and within seconds finds visually similar cases, including their descriptions. This way radiologists for the first time can efficiently browse through the PetaBytes of existing medical image data, and also get easy access to case relevant reference information and online literature. The contextflow 3D image search engine brings the information closer to the point of care and supports radiologists, so that they can focus on diagnosing their patient images instead of wasting valuable time searching for information.
Shipping has never been this easy
Byrd is an first mile logistics service that allows businesses and individuals to ship their items with one click. Customers can connect their online stores directly with byrd, which allows them to easily import their order data and ship items with one click. As soon as a pickup is requested, a byrd courier will pick up the items and bring them to the byrd warehouse, where they will be packaged and shipped at the best available rate. byrd is currently available in Vienna and Berlin."
Streaminr is a data analytics startup specializing in the prediction of supply chain risks. We target enterprises with complex supply chain networks facing disruption risks at thousands of distributed suppliers sites and transport hubs. With Streaminr, we develop a technology for automated discovery of disruption risks that helps enterprises to detect risks in supply chains early and enables them to plan mitigation activities in time. Streaminr relies on artificial intelligence trained to identify signals of upcoming potential disruptive events in social media data. Our prototype detects labor strike risks in Indonesia based on Twitter data and uses advanced natural language processing and machine learning technology developed by Lisa Madlberger in her PhD research at TU Wien in collaboration with University of Indonesia and Institute of Technology in Bandung. To bring this technology to the market, Lisa teamed up with her co-founder Harald Nitschinger, who brings in his experience in enterprise software sales. Streaminr joined the TUW Incubator in 2015 with the goal to develop cutting edge AI technology for event prediction.
Huber Scientific develops novel solutions for experimental equipment used in the fields of Electrochemistry and Solid State Ionics. These innovative setups not only enable completely new experiments, but also allow for the first time a combination of different, complementary methods.
Huber Scientific will also supply completely new designed and improved test equipment for standardized measurements, which is much easier to repair, simpler to use and much cheaper than other test stations already available on the market. Up until now, research groups worldwide had to develop and build their own measurement equipment since for many experiments no commercial setups were available. This often resulted in makeshift equipment of varying quality with no long term support.
With years of experience in designing high quality and easy to use and upkeep experimental equipment, Huber Scientific will help research groups all over the world to focus on what they are doing best: Delivering top notch science.
We aim on making revenue on the basis of an add-on for process analytical technology in the industrial environment. Our sound cage exploits ultrasonic fields to exert forces on suspended particles and thus enhance the stability, sensitivity, specificity and other parameters of industrial sensing/analytical devices. It enables various – often optical – sensing schemes to be applied in-line, i.e. directly within the reaction vessel or media stream and real-time, i.e. without the need of sample taking or time-consuming preparation protocols.
The device can be applied to enhance the controlling/steering of processes in various industries reaching from pharmaceutical or biotechnological production over food/beverages and cosmetic products to oil industry and wastewater treatment. The improvement brought about by the sound cage is targeting on the increase of product yield and product quality.
UAVs, commonly called drones, are getting increasingly popular, not only for amateurs, but also for a growing number of commercial applications. Autonomous flight, where the drone is not guided by a human operator, has great potential in a lot of fields, from various applications in logistics to inspection tasks.
Unfortunately, drones are not aware of their environment. Autonomous flight requires knowledge of the surroundings, in order to detect and avoid obstacles. Drones are not capable of this yet, which inhibits fully autonomous operation.
Currently there is no reliable and affordable solution for environment scanning. Existing affordable approaches have flaws: Ultrasonic sensors vaguely detect obstacles but do not provide sufficient resolution. Image processing methods require much processing power and are error prone. Well performing approaches based on ranging techniques are expensive.
This changes with arsa, an environment scanner based on laser ranging measurements, presenting a reliable and affordable solution for precise environment scanning, which will finally enable fully autonomous operation of UAVs at low cost.