Abstract: An apparatus and method for inspecting a vehicle include photographing a lower side of a vehicle to obtain a lower side image, transmitting the lower image to a server, receiving inspection result data of the lower side of the vehicle from the server, and displaying the inspection result data on a display, wherein the received inspection result data includes a result obtained by generating a defect image of the lower side of the vehicle from a virtual image, in which a defect is indicated, of a reference lower image of the vehicle, and determine whether the lower side of the vehicle is defective using the generated defect image.

Abstract: Provided is a method of estimating a relationship between objects through machine learning, the method comprising receiving a scan image, recognizing a starting point of a relationship line and an object code in the scan image, determining whether a relationship line is present between the recognized starting point and the recognized object code, and, based on determining that the relationship line is present, transmitting a combination of the starting point and the object code connected with the relationship line to a database.

Abstract: An instance segmentation model training method includes training the instance segmentation model firstly based on a first data set stored in a first database, and training the firstly-trained instance segmentation model secondly based on a second dataset stored in a second database, where the second dataset includes a large-scale open-source dataset and a segmentation target object-absent image acquired by capturing a working environment within an industrial site.

Abstract: An apparatus may comprise a processor, and memory storing instructions, that when executed by the processor, may cause the apparatus to extract at least one source instance from at least one source image stored in a dataset, arrange the at least one extracted source instance on a target image stored in the dataset, wherein the target image may comprise at least one target instance associated with a ground-truth mask used to recognize the at least one target instance, perform, based on the arrangement, an augmentation process on the target image, adjust the ground-truth mask value based on the performance of the augmentation process, and output the target image including the adjusted ground-truth mask of the target instance.

Abstract: A method of training a knowledge distillation based continual semantic segmentation model may include training the continual semantic segmentation model based on training data, predicting a probability for each class of an output of a current continual semantic segmentation model that has been generated by being trained and a probability for each class of an output of an old continual semantic segmentation model, expanding a class related to the old continual semantic segmentation model so that a spatial dimension of a class related to the old continual semantic segmentation model is the same as a spatial dimension of a class related to the current continual semantic segmentation model, calculating knowledge distillation loss based on the predicted probability for each class, and updating the current continual semantic segmentation model based on the knowledge distillation loss.

Abstract: An apparatus and method for inspecting a vehicle include photographing a lower side of a vehicle to obtain a lower side image, transmitting the lower image to a server, receiving inspection result data of the lower side of the vehicle from the server, and displaying the inspection result data on a display, wherein the received inspection result data includes a result obtained by generating a defect image of the lower side of the vehicle from a virtual image, in which a defect is indicated, of a reference lower image of the vehicle, and determine whether the lower side of the vehicle is defective using the generated defect image.

Abstract: A device for inspecting a vehicle is provided to inhibit side effects of vehicle inspection caused by human errors by determining whether the vehicle is defective according to relative positions of a plurality of objects in an obtained bottom image of the vehicle. The device for inspecting the vehicle includes a first camera that is configured to obtain a bottom image of the vehicle and a processor. The processor recognizes at least one first object and at least one second object in the bottom image of the vehicle, and determines whether the vehicle is defective based on relative positions of the first object and the second object.

Abstract: Systems and methods are discussed to automatically create a domain ontology that is a combination of ontologies. Some embodiments include systems and methods for developing a combined ontology for a website that includes extracting collocations for each webpage within the website, creating first and second ontologies from the collocations, and then aggregating the ontologies into a combined ontology. Some embodiments of the invention include unique ways to calculate collocations, to develop a smaller yet meaningful document sample from a large sample, to determine webpages of interest to users interacting with a website, and to determine topics of interest of users interacting with a website. Various other embodiments of the invention are disclosed.

Abstract: Systems and methods are discussed to automatically create a domain ontology that is a combination of ontologies. Some embodiments include systems and methods for developing a combined ontology for a website that includes extracting collocations for each webpage within the website, creating first and second ontologies from the collocations, and then aggregating the ontologies into a combined ontology. Some embodiments of the invention include unique ways to calculate collocations, to develop a smaller yet meaningful document sample from a large sample, to determine webpages of interest to users interacting with a website, and to determine topics of interest of users interacting with a website. Various other embodiments of the invention are disclosed.