Jheng-Ying Yu

Enhanced canonical correlation analysis with local density for cross-domain visual classification

Real-world visual classification tasks typically need to deal with data observed from different domains. Inspired by canonical correlation analysis (CCA), we propose an enhanced CCA with local density for associating and recognizing cross-domain data. In addition to maximizing the correlation of the…