The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
— We address the problem of learning terrain traversability properties from visual input, using automatic mechanical supervision collected from sensors onboard an autonomous vehi...
Anelia Angelova, Larry Matthies, Daniel M. Helmick...
The Robinson curriculum contains a novel approach to improve the engineering education, to enhance technological literacy of students from nonengineering fields and to increase in...
Sabina Jeschke, Lars Knipping, Marcus Liebhardt, F...
We present a novel approach to estimating depth from single omnidirectional camera images by learning the relationship between visual features and range measurements available dur...