Keita Tomochika

Fully Automated Annotation With Noise-Masked Visual Markers for Deep-Learning-Based Object Detection

Automated factories use deep-learning-based vision systems to accurately detect various products. However, training such vision systems requires manual annotation of a significant amount of data to optimize the large number of parameters of the deep convolutional neural networks. Such manual annotat