Abstract: The present disclosure relates to an optical laminate for a flexible display device comprising: a support substrate layer; and a hard coating layer positioned on at least one surface of the support substrate layer and having a thickness of 10 ?m to 250 ?m, wherein the hard coating layer is a polysiloxane containing 70 mol % or more of a repeating unit including an epoxy group-containing functional group; and an elastomeric polymer including polycaprolactone polyol, and wherein the polysiloxane has a number average molecular weight of more than 3,000 and less than 10,000, and a polydispersity Index (PDI) of 1.0 or more and less than 5.0, and a flexible display device including the same.

Abstract: Provided are an apparatus for collecting a training image of a deep learning model and a method for the same. The apparatus may include a camera sensor configured to capture an image of a surrounding of a vehicle and a controller configured to determine an entropy of each pixel in the image. The controller may also be configured to determine an entropy of each class in the image based on the entropy of each pixel in the image and determine whether to collect the image based on the entropy of each class.

Abstract: An apparatus and method for detecting performance degradation of an autonomous vehicle include a storage configured to store a deep learning model used for image recognition in the autonomous vehicle and a controller configured to determine entropy of each pixel among a plurality of pixels in an output image of the deep learning model, determine an average value of the entropy of the plurality of pixels, and detect performance degradation of the deep learning model based on the average value of the entropy of the plurality of pixels.

Abstract: A device and a method for tracking an object are disclosed. The device includes a camera for acquiring an external environment image of a vehicle and a controller. The controller extracts a detected object from the external environment image, generates an estimated object by predicting a next position of the detected object, assigns an ID to the detected object based on an intersection over union (IOU) between the estimated object and the detected object, assigns a weight based on a detection frequency of each of the IDs, and generates the estimated object based on the weight.

Abstract: A device for detecting a road marking and a method thereof. The device includes a camera that photographs a road image, and a controller that detects class information of plural pixels in the road image, recognizes lines based on the class information of each pixel, and detects a road marking located between the recognized lines.