Jacob Huh

Unsupervsied Deep Multimodal Learning for Object Detection

Recent advances in the artificial neural networks have shown immense success in the computer vision field. While supervised learning tasks in object detection has shown to be a feasible task, the necessity of the supervision in the task is not observed in humans. Despite the fact that object Information is a unison of all senses, currently, object detection tasks are restricted to visual data. I will be researching on using multi modal data to tackle object detection in a supervised and unsupervised setting.

Message to Sponsor

I would like to thank the Rose Hills Foundation for funding my research stipend. The donation allows me to focus on my work and alleviate financial problems over the summer. As a senior, the stipend allows me to conclude my undergraduate career with a project that encompasses all my knowledge that I have gained throughout the years.
  • Major: Electrical Engineering and Computer Science
  • Sponsor: Rose Hills Independent
  • Mentor: Alexei A. Efros