Towards robust visual recognition: learning from imperfect data - Hu, Xinting (Nanyang Technological University, 2023)
Though Deep Convolutional Neural Networks (DCNN) have shown success in many tasks in the field of computer vision, the huge effort made in constructing large-scale annotated datasets is indispensable. Even the prevailing models can fail when the dataset does not cover enough samples. For example, for the most fundamental vision task -- classification task, when we shrink the dataset size in half, the error rates are doubled.