Three problems in computer vision: design, fabrication and analysis of paper sensors for detecting food contaminants, segmentation of food crystal images, and zero-shot action recognition in video sequences.

This dissertation delves into three projects within the realms of image processing, computer vision, and machine/deep learning. The primary objective of the first project is the detection of heavy metal particle concentrations using microfluidic paper-based devices. The second project revolves around the analysis of crystals within microscopic images. The third project centers around zero-shot action recognition in video sequences, utilizing a multi-modality deep learning framework that is refined through prompt tuning to enhance its performance.