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Developing a Snow Detection Algorithm Using Spatial Attention for Pedestrian Safety
Master's Thesis Paper
Ricardo de Deijn
Data Scientist Computer Vision Engineer AI Researcher
Data Scientist Computer Vision Engineer AI Researcher
I'm an AI Engineer and Data Scientist, originally from The Netherlands. I earned my Master's in Data Science at Minnesota State University, Mankato, where I graduated top of my class. Previously, I completed my Bachelor's in ICT at HZ University of Applied Sciences in The Netherlands, with an Erasmus+ minor in Computer Science in Austria. My master's thesis focused on real-time snow detection using deep learning to enhance pedestrian safety. Currently, I'm seeking research-focused positions in computer vision and AI, aiming to contribute to cutting-edge developments as a Research Scientist.
My expertise lies in AI, computer vision, and generative models, with a strong research interest in autonomous AI and real-world applications of deep learning.
My research has been published at conferences, such as MWAIS, AIMLA, and CADSCOM, and my work explores innovative applications of AI, particularly in enhancing safety and automation. I am passionate about the intersection of deep learning and real-time systems.
Master's Thesis Paper
Best Paper at CADSCOM 2024 Conference, fast-tracked for JMWAIS journal
Published at MWAIS 2024, co-authored with Dr. Rajeev Bukralia
Published at AIMLA 2024 Conference
I'll be presenting my latest research on AI applications in data science at this year's Data Tech Conference. Join me to learn more about the transformers architecture in both language and vision applications.
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A mobile AI system that detects snow in real-time using spatial attention-based CNNs.
Researching how pre-trained prompt-based models and inverse diffusion models can improve synthetic data generation for snow detection training datasets.
Read about my recent research projects and current developments...
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Read about my wins and experiences from my participations at Hackathons...
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Featured speaker at Data Tech Conference (2024-2025) and DREAM student organization events
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