Abstract: Disclosed herein are an apparatus and method for classifying clothing attributes based on deep learning. The apparatus includes memory for storing at least one program and a processor for executing the program, wherein the program includes a first classification unit for outputting a first classification result for one or more attributes of clothing worn by a person included in an input image, a mask generation unit for outputting a mask tensor in which multiple mask layers respectively corresponding to principal part regions obtained by segmenting a body of the person included in the input image are stacked, a second classification unit for outputting a second classification result for the one or more attributes of the clothing by applying the mask tensor, and a final classification unit for determining and outputting a final classification result for the input image based on the first classification result and the second classification result.

Abstract: An apparatus for manufacturing a display device includes a gas exhaust unit and a gas spray unit. The gas exhaust unit includes first and second sidewalls disposed side by side along a first direction, and an upper plate disposed on the first and second sidewalls, a first partition disposed between the first and second sidewalls and extending away from a lower surface of the upper plate in a second direction. The gas spray unit includes first and second spray portions spraying first and second gases in the second direction. The first partition includes first and second surfaces, a third surface connecting the first surface to the second surface, first and second horizontal openings formed at the first and second surfaces, a first vertical opening formed at the third surface, and a first sub exhaust path connecting the first and second horizontal openings, and the first vertical opening with each other.

Abstract: An electrode including a current collector; and an electrode active material layer disposed on at least one surface of the current collector is disclosed. The electrode active material layer includes a lower layer region facing the current collector, and an upper layer region facing the lower layer region and extended to the surface of the electrode active material layer. The lower layer region includes a first active material and a first non-rubbery binder and is free from a rubbery binder. The upper layer region includes a second active material, a second non-rubbery binder, and a rubbery binder. The rubbery binder is a hydrogenated nitrile butadiene rubber (H-NBR). Each of the first non-rubbery binder and the second non-rubbery binder includes a polyvinylidene fluoride (PVDF)-based polymer, and the weight ratio of the second non-rubbery binder to the rubbery binder in the upper layer region is 1:0.03-1:0.07.

Abstract: Provided are an artificial intelligence insurance server and a method for providing an artificial intelligence insurance service. The artificial intelligence insurance server comprises a receiving unit for receiving input data including medical data of an insurance user, a comparison data selection unit for selecting comparison data based on the input data, and deriving first analysis data by analyzing the comparison data, an artificial intelligence analysis unit for obtaining second analysis data derived by performing artificial intelligence analysis on the input data, a comparison unit for comparing the first and the second analysis data and generating final analysis data using the first and the second analysis data and a decision-making unit for making at least one insurance-related decision using the final analysis data.

Abstract: The present invention relates to a classification apparatus for pathologic diagnosis of a medical image and a pathologic diagnosis system using the same. According to the present invention, there is provided a classification apparatus for pathologic diagnosis of a medical image, including: a feature extraction unit configured to extract feature data for an input image using a feature extraction variable; a feature vector transformation unit configured to transform the extracted feature data into a feature vector using a vector transform variable; and a vector classification unit configured to classify the feature vector using a classification variable, and to output the results of the classification of pathologic diagnosis for the input image; wherein the feature extraction unit, the feature vector transformation unit and the vector classification unit are trained based on a first tagged image, a second tagged image, and an image having no tag information.

Abstract: The present invention relates to a classification apparatus for pathologic diagnosis of a medical image and a pathologic diagnosis system using the same. According to the present invention, there is provided a classification apparatus for pathologic diagnosis of a medical image, including: a feature extraction unit configured to extract feature data for an input image using a feature extraction variable; a feature vector transformation unit configured to transform the extracted feature data into a feature vector using a vector transform variable; and a vector classification unit configured to classify the feature vector using a classification variable, and to output the results of the classification of pathologic diagnosis for the input image; wherein the feature extraction unit, the feature vector transformation unit and the vector classification unit are trained based on a first tagged image, a second tagged image, and an image having no tag information.

Abstract: The present invention relates to a cloud-based pathological analysis system and method. The present invention provides a cloud-based pathological analysis system, including: a client device coupled to a microscope, and configured to acquire an image for a tissue sample via the microscope and generate a sample image; and a cloud server coupled to the client device over a network, and configured to receive sample image data from the client device over the network and store the sample image data; wherein the cloud server analyzes the received sample image data, and transmits analysis information to the client device.

Abstract: A visual product searching apparatus includes a product area determining part, a visual word generating part and a product searching part. The product area determining part extracts a product area in an input image. The visual word generating part generates a visual word reflecting human visual cognitive characteristics based on the product area. The product searching part searches a product using the visual word.