Abstract: A device for recognizing an obstacle of a vehicle includes a camera for acquiring an image, a detection device for extracting an object by applying a convolutional neural network to the image, a center calculation device for estimating a center point and a region outside the center point of the extracted object, an uncertainty determination device for determining whether the estimated center point and region outside the center point are uncertain, and a condition determination device for determining whether travel is possible based on the determined uncertainty.

Abstract: A device for recognizing an obstacle of a vehicle includes a camera for acquiring an image, a detection device for extracting an object by applying a convolutional neural network to the image, a center calculation device for estimating a center point and a region outside the center point of the extracted object, an uncertainty determination device for determining whether the estimated center point and region outside the center point are uncertain, and a condition determination device for determining whether travel is possible based on the determined uncertainty.

Abstract: A class labeling system for autonomous driving includes a detection module, a segmentation module, and a lane road boundary detection module. The detection module is configured to detect objects for autonomous driving from an image captured by a camera to generate a bounding box for each of the objects and detect property information about the object. The segmentation module is configured to determine classes for each pixel of the bounding box detected by the detection module and process at least one of the classes as don't care. The lane road boundary detection module is configured to detect at least one of lane and road boundaries using the bounding box detected by the detection module.

Abstract: A device for recognizing an obstacle of a vehicle includes a camera for acquiring an image, a detection device for extracting an object by applying a convolutional neural network to the image, a center calculation device for estimating a center point and a region outside the center point of the extracted object, an uncertainty determination device for determining whether the estimated center point and region outside the center point are uncertain, and a condition determination device for determining whether travel is possible based on the determined uncertainty.

Abstract: A class labeling system for autonomous driving includes a detection module, a segmentation module, and a lane road boundary detection module. The detection module is configured to detect objects for autonomous driving from an image captured by a camera to generate a bounding box for each of the objects and detect property information about the object. The segmentation module is configured to determine classes for each pixel of the bounding box detected by the detection module and process at least one of the classes as don't care. The lane road boundary detection module is configured to detect at least one of lane and road boundaries using the bounding box detected by the detection module.