[Master Thesis(Research)] Enhance data selection efficiency with variational auto-encoder for object detection’s active learning Abstract: • It can save 70% labeled cost for achieving a usable model in diverse domains and rare events. • Uncertainty and diversity information are important for active learning. • VAE can provide good representation for known the unlabeled data distribution in surveillance cameras. Reference: Document: https://etd.lib.nctu.edu.tw/cgi-bin/gs32/hugsweb.cgi?o=dnthucdr&s=id=%22G021060617050%22.&searchmode=basic