Ing. Stanislav Kuznetsov, Ph.D.

2015

The project focuses on perspective and ever-expanding field of data processing and extraction of information of valuable content from the data. The methods for information extraction are increasingly using selected methods of artificial intelligence such as neural networks and evolutionary algorithms. Combined models or algorithms for text processing (text mining) come to the fore. The need of these topics is evident from the fact that each year, the volume of data is doubling. At the same time, only 20 % of the available data are processed.

2016

The project is focused on data mining of non-structured data from large-scale sources. The data are represented by textual and image/video information. To porcess the data, selected methods of artificial intelligence such as neural networks/deep learning, evolutionary algorithms and methods of image processing will be used. The need of these topics is evident from the fact that each year, the volume of data is doubling. At the same time, only 20 % of the available data are processed.

2023

Projekt má přímou vazbu na cíle Inovační strategie České republiky 2019–2030 v oblasti ochrany duševního vlastnictví, a to zejména na cíle týkající se zvýšení povědomí o ochraně duševního vlastnictví a využívání patentových informací. Projekt podpoří informovanost veřejnosti o problematice duševního vlastnictví, usnadní přípravu přihlášek k předmětům průmyslové ochrany, využije dostupné patentové informace a umožní snížit nároky na kapacitu pracovní síly a poskytnout nepřetržitý servis interním a externím zákazníkům. Účelem je kvalitnější a efektivní výkon státní správy. Hlavními cíli projektu je vyvinout systém obsahující bázi znalostí zachycující obecné informace ke správnímu řízení.

2023 - 2025

The EDIH CTU represents a major European Digital Innovation Hub in the Czech Republic in the field of Artificial Intelligence (AI) and Machine Learning (ML) transferring trustworthy solutions and services to the industry, health, transportation and energy sectors. The EDIH CTU, with its vision "Inspire & Make the Czech AI-driven Industry", aims to become the innovation and technology leader in providing professional AI/ML services for the local SMEs, small mid-caps and public sector organizations with respect to their digital and green transformation. The strong consortium partners representing academia, business sector and key associations of enterprises in the Czech Republic provide sufficient know-how, expertise and state-of-the-art experimental facilities to serve the needs of the public and private sector at the national and also international level. The major focus is on promoting digital transformation adoption, providing high-quality services, education and knowledge sharing, pursuing ecosystem development, and establishing strong inter-EDIH collaboration. The consortium builds upon already existing partnerships in AI and manufacturing enabling best practice sharing, expertise exchange, and joint activities seeking far-reaching synergies thus strengthening the far-reaching impacts of the European network of EDIHs.

2017 - 2019

The project focuses on perspective and ever-expanding field of data processing and extraction of information of valuable content from the data. The methods for information extraction are increasingly using selected methods of artificial intelligence such as neural networks and evolutionary algorithms. Combined models or algorithms for text processing (text mining) come to the fore. The need of these topics is evident from the fact that each year, the volume of data is doubling. At the same time, only 20 % of the available data are processed.

2014

The project focuses on perspective and ever-expanding field of data pre-processing and extraction of information of valuable content from the data. The methods for information extraction are increasingly using selected methods of artificial intelligence such as neural networks and evolutionary algorithms. Combined models or algorithms for text processing (text mining) come to the fore. The need of these topics is evident from the fact that each year, the volume of data is doubling. At the same time, only 20 % of the available data are processed.