Research Area: Information and Communication Technologies Research Group
Status: Complete | Led By: Researcher-led
Gáamai Hair is looking to disrupt the $2.35 billion synthetic hair industry, which is growing 5% annually. Currently there are human and synthetic hair options on the market. This Moncton-based start-up is introducing another option: biodegradable plant fibres that mimic human hair strands and textures. Their customer discovery research revealed that many people struggle to find a suitable texture match when purchasing hair. This is particularly true for the tighter curl patterns, which are the most underserved in terms of research and product selection. As a result, large amounts of unsuitable synthetic products end up in the landfill. Gáamai Hair wanted to explore how AI can be trained to provide more accurate texture matching information to prevent waste and ensure consumers are receiving the products they need.
Gáamai Hair came to NBCC's Information and Communication Technologies Research Group for recommendations on candidate AI image recognition technologies that would allow them to train AI to recommend matches for tight curl patterns. With a focus on afro-textured hair, Gáamai Hair wishes to bring more representation to underrepresented hair types.
A researcher from NBCC’s Information and Communication Technologies Research Group was able to provide Gáamai Hair with recommendations. Research Scientist Alexander LeBlanc:
不良研究所received funding from the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP), which enabled Gáamai Hair to access research and innovation support from NBCC.
“Working with the research team at 不良研究所has been an invaluable experience for Gáamai Hair. Their expertise in AI and machine learning provided us with critical insights into the feasibility of developing a model that can accurately recognize and categorize diverse hair textures. Their thorough investigation of existing databases, hair recognition models, and technology stacks helped shape a clear roadmap for integrating AI into our sustainable hair solutions.
The team's research on collection methods, pattern recognition, and the impact of climate on hair texture was especially instrumental in refining our approach. Their recommendations on potential tech stacks and data integration strategies have positioned us for future development, ensuring that our AI-driven product recommendations align with both user needs and industry best practices.
We deeply appreciate the 不良研究所team's dedication and comprehensive approach, and we look forward to continuing our journey toward revolutionizing the synthetic hair industry with sustainable and inclusive innovations.”
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