Project “Development of a new method for detection and identifying bacterial colonies using artificial neural networks and Machine Learning algorithms” is co-financed from European Union funds under the European Regional Development Funds as part of the Smart Growth Operational Programme.
Project implemented as part of the National Centre for Research and Development: Fast Track.
Programme
Smart Growth Operational Programme
Action
1.1. R+D projects
Fund
European Regional Development Fund
Perspective
2014 – 2020
About the project
The aim of the project is to develop a new method for detection and identifying bacterial colonies using artificial neural networks and Machine Learning algorithms. The goal is to automate the analysis of bacterial culture colonies on Petri dishes, in particular, the classification of the type of sown bacteria and counting the number of bacterial colonies. The algorithms will be based on deep learning methods which, according to current scientific knowledge, are best suited for the recognition of images and can be used to identify the key morphological features of bacterial colonies. In cooperation with a microbiology expert, a training database will be prepared to match the parameters of artificial neural networks. The database will contain carefully described photos of Petri dishes, on which bacterial strains were sown, and which can be used in the supervised learning process. Additional information about the samples will be provided by spectral analysis and a three-dimensional map of vertices made by the laser scanning method. The final product will be specialized software for the analysis of bacterial cultures.
Name of the beneficiary
NeuroSYS
Project value
2 437 811,10 zł
Co-financing from the EU
1 850 331,93 zł
Voivodeship
dolnośląskie
County
m. Wrocław
Project “The development of a supporting system for maintenance departments of manufacturing companies, using augmented reality (AR) technology and elements of artificial intelligence (AI)” is co-financed from European Union funds under the European Regional Development Funds as part of the Smart Growth Operational Programme.
Project implemented as part of the National Centre for Research and Development: Fast Track.
Programme
Smart Growth Operational Programme
Action
1.1.1 R+D projects
Fund
European Regional Development Fund
Perspective
2014 – 2020
About the project
The aim of the project is to create a system that will support the work of maintenance departments of manufacturing companies, using augmented reality (AR) technology and elements of artificial intelligence (AI). It will increase the efficiency of employees working with advanced production machines (maintenance engineers, service technicians, automation service engineers) and will facilitate the transfer of knowledge and reduce the level of training required for effective service work. It can also be used as a training platform for new employees (standardized ‘hands-on’ training using AR glasses) as well as a tool supporting the work of engineers (easy, immediate access to key information in the workplace).
Name of the beneficiary
NeuroSYS
Project value
3 399 503,70 zł
Co-financing from the EU
2 616 473,22 zł
Voivodeship
dolnośląskie
County
m. Wrocław
Project “The development of automatic knowledge structuring methods by analyzing semantic relations in teaching materials of various content types for an LMS (Learning Management System) platform” is co-financed from European Union funds under the European Regional Development Funds as part of the Smart Growth Operational Programme.
Programme
Smart Growth Operational Programme
Action
1.1.1 R+D projects
Fund
European Regional Development Fund
Perspective
2014 – 2020
About the project
The project objective is to create an automated content organization module to be implemented in learning management system (LMS) developed by the applicant. The algorithms for content extraction and analysis will be based on the current state-of-the-art natural language processing (NLP) methods. An LMS system is a set of tools used to create and distribute teaching materials, and manage employees training process in large organization, like corporations, government organizations, or educational institution. It can be used to define learning tracks and oversee the training process of thousands of users at the same time. Implementing LMS in the organization decreases the training process costs and new employees onboarding time. Teaching materials in an LMS system do not form a knowledge base with logic and contextual connections. Thus, an employee can not use an LMS system as a knowledge base to quickly find answers, even though this knowledge is there in the form of courses. The goal of the research and development phase is to produce an NLP-based module for content extraction and determining semantic similarity. The first part is necessary because teaching materials in LMS systems can be uploaded as HTML websites, PDF documents, audio / video recordings, or SCORM packages. The latter will link problems and questions with relevant parts of courses. The developed methods will be implemented in the applicant’s LMS system to increase its functionality and competitiveness. They will make it possible to search for particular fragments from courses base to find an answer for questions asked by users. They will allow to point which materials a user should redo by finding relevant fragments related to incorrectly answered questions in a quiz. They will help to create assessments by identifying quiz problems which are not discussed within given learning track.
Name of the beneficiary
NeuroSYS
Project value
6,922,492.80 zł
Co-financing from the EU
5,206,078.29 zł
Voivodeship
dolnośląskie
County
m. Wrocław
