8 research outputs found
Recursive Video Lane Detection
A novel algorithm to detect road lanes in videos, called recursive video lane
detector (RVLD), is proposed in this paper, which propagates the state of a
current frame recursively to the next frame. RVLD consists of an intra-frame
lane detector (ILD) and a predictive lane detector (PLD). First, we design ILD
to localize lanes in a still frame. Second, we develop PLD to exploit the
information of the previous frame for lane detection in a current frame. To
this end, we estimate a motion field and warp the previous output to the
current frame. Using the warped information, we refine the feature map of the
current frame to detect lanes more reliably. Experimental results show that
RVLD outperforms existing detectors on video lane datasets. Our codes are
available at https://github.com/dongkwonjin/RVLD.Comment: ICCV 2023 accepte
New gene selection method for classification of cancer subtypes considering within-class variation
AbstractIn this work we propose a new method for finding gene subsets of microarray data that effectively discriminates subtypes of disease. We developed a new criterion for measuring the relevance of individual genes by using mean and standard deviation of distances from each sample to the class centroid in order to treat the well-known problem of gene selection, large within-class variation. Also this approach has the advantage that it is applicable not only to binary classification but also to multiple classification problems. We demonstrated the performance of the method by applying it to the publicly available microarray datasets, leukemia (two classes) and small round blue cell tumors (four classes). The proposed method provides a very small number of genes compared with the previous methods without loss of discriminating power and thus it can effectively facilitate further biological and clinical researches