Canada Spends Logo

Explorez notre analyse du budget 2026

Grant: Alliance Grants

Concordia University

$60,000.00

Computer Vision for Information Extraction from Document Images

EF 2024-25

Résumé
Our project aims to develop an advanced system for understanding Safety Data Sheets (SDS) using artificial intelligence (AI) and computer vision techniques. SDS documents contain important information about chemicals and their environmental impact. Currently, the data in SDS documents are manually entered into a database, which is time-consuming and prone to errors. We propose using AI to automatically extract information from SDS documents, such as text, images, and product specifications. This will streamline the process and improve accuracy. This project will be done in collaboration with the partner company, ERA Environmental. The project will include internships where students will work directly with the company, gaining hands-on experience in AI and computer vision. The outcomes of this project will have significant benefits for Canada. By automating the extraction and analysis of SDS data, we will improve efficiency and reduce errors in environmental reporting. This will help companies comply with regulations and promote sustainable practices. The project will also contribute to the advancement of AI and computer vision technologies, positioning Canada as a leader in this field. After completing the project, the partner company plans to integrate the developed system into its existing infrastructure and further enhance its capabilities. This will ensure the project's results have a lasting impact in Canada.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
586804-2023
Name nom
Wang, Yang Y
Department département
Computer Science and Software Engineering
Organization id
70
Institution établissement
Concordia University
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
60000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
801
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Computer software
Area of application fr
Logiciel
Research subject code
2800
Research subject group en
Artificial intelligence
Research subject group fr
Intelligence artificielle
Research subject en
Artificial intelligence (computer vision, use2603)
Research subject fr
Intelligence artificielle (vision artificielle, utiliser 2603)
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Computer Vision for Information Extraction from Document Images
Keywords
computer vision; document understanding and analysis; image processing; machine learning
Application summary
Our project aims to develop an advanced system for understanding Safety Data Sheets (SDS) using artificial intelligence (AI) and computer vision techniques. SDS documents contain important information about chemicals and their environmental impact. Currently, the data in SDS documents are manually entered into a database, which is time-consuming and prone to errors. We propose using AI to automatically extract information from SDS documents, such as text, images, and product specifications. This will streamline the process and improve accuracy. This project will be done in collaboration with the partner company, ERA Environmental. The project will include internships where students will work directly with the company, gaining hands-on experience in AI and computer vision. The outcomes of this project will have significant benefits for Canada. By automating the extraction and analysis of SDS data, we will improve efficiency and reduce errors in environmental reporting. This will help companies comply with regulations and promote sustainable practices. The project will also contribute to the advancement of AI and computer vision technologies, positioning Canada as a leader in this field. After completing the project, the partner company plans to integrate the developed system into its existing infrastructure and further enhance its capabilities. This will ensure the project's results have a lasting impact in Canada.