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Jorian Bos posted this:
Other at EIT Digital

STRUCTR - Low-Code Dev. Platform combined with Graph Technology LESS CODE MORE APPLICATION: Structr is the unique low code platform, which uses graph technology and is open source. Our goal is to deliver best-quality, innovative solutions and individual software development. The brand Structr was established in 2010 when Axel started the software project of the same name. In 2011, when his brother Christian joined the project, the two brothers founded a company which has been renamed to Structr GmbH in 2015. The visualization of the data and program structures as a graph accelerates the development and makes the results easily comprehensible for everyone at any time. Since 2010, we have been supporting companies around the globe in their digital transformation by implementing projects based on our unique Structr software platform. What makes Structr special is that not only the data itself but also the entire definition of the software application built with the Structr platform is stored in a graph database.

STRUCTR - Low-Code Dev. Platform combined with Graph Technology

Jorian Bos posted this:
Other at EIT Digital

SYNERISE - Next Generation AI Marketing Cloud Synerise is an end-to-end platform that uses data and AI to help brands better respond to the needs of their customers, through automation applications, business intelligence reporting, communication and personalization tools, and pricing policy management. All in real-time and at scale, regardless of the size of operations. Synerise is used by 100+ enterprise-scale companies including Orange, Carrefour, mBank, Żabka.

SYNERISE - Next Generation AI Marketing Cloud

Unitat de Valorització de la URV posted this:
Licensing Manager at Fundació URV

Automatic feature descriptor in agriculture images using neural networks Software that recognizes user-defined objects in aerial images for agriculture and derives quantitative estimators for plant count (N), green area index (GAI), growth stage (GS), deficient leaf area fraction (DLAF), and weeds area fraction (WAF), and potentially further measures. It employs a pre-trained multi-layer neural network model to classify regions of an image. The network is trained based on good examples of distinct types of objects that are provided by experts in aerial photography for agriculture. Afterwards, any provided aerial image or video can be analyzed with the pretrained software trained once.

AZAM KHAN posted this:
Co-Founder and COO at LexSet.ai

Synthetic data for Computer Vision applications At LexSet, we create fully annotated, bespoke, synthetic datasets that improve Computer Vision accuracy and unlock new use cases. We also offer full stack solutions including trained models and hosted CV systems.. We’re working on teaching AIs the full spectrum of possibilities — and producing superior results. We have achieved classification accuracy up to 99% without the use of real-world data in the training set. Reach out to us today to find out why our clients refer to our results “Pretty Darn Amazing” — Principal Engineer, Major American Robotics Company, and LexSet Client.