Abstract: The present invention relates to a release layer for a metal foil with carrier and a metal foil with carrier including the release layer. The release layer is designed for easy removal of the carrier and includes one or more nitrogenous heterocyclic compounds and one or more inorganic compounds containing at least one metal selected from the group consisting of nickel, molybdenum, cobalt, phosphorus, manganese, and iron.

Abstract: An X-ray imaging apparatus includes an imaging device configured to capture a camera image of a target; a controller configured to stitch a plurality of X-ray images of respective divided regions of the target to generate one X-ray image of the target; and a display configured to display a settings window that provides a GUI for receiving a setting of an X-ray irradiation condition for the respective divided regions, and display the camera image in which positions of the respective divided regions are displayed.

Abstract: It is disclosed a blood glucose prediction system and method using saliva-based artificial intelligence deep learning technique.

Abstract: A catheter-type ultrasound endoscope according to an embodiment of the present invention includes an ultrasound module for acquiring an ultrasound image, and a biopsy needle, wherein the ultrasound module includes a pMUT module and an ASIC signal processing circuit, and the ASIC signal processing circuit uses CMOS-MEMS technology. This steerable catheter-type ultrasound endoscope capable of performing tissue biopsies according to the present invention obtains ultrasound images from representative digestive organs, such as the bile duct and the pancreatic duct, through the miniaturization of the ultrasound module, and performs a biopsy while the ultrasound images are observed in real time, and thus can improve the accuracy of diagnosis.

Abstract: A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

Abstract: A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

Abstract: Methods and systems for selecting listing based on a click predictions score are disclosed. The server system includes one or more processors, memory, and one or more programs stored in the memory. The server system receives a search query from a client system. In response to receiving the search query, the server system identities a plurality of item listings relevant to the received search query. For each identified item listing, the server system generates a click prediction score, wherein a click predication score represents the estimated likelihood that a user will click on the listing. The server system ranks the plurality of item listings based on the generated click prediction score and selects a predetermined number of the item listings for transmission to the client system based on their ranking and associated click prediction score. The server system transmits one or more item listings to the client system for display.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

Abstract: A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.

Abstract: Three-dimensional image data is generated. According to an example embodiment, three-dimensional depth information is estimated from a still image. A set of monocular images and their corresponding ground-truth depth maps are used to determine a relationship between monocular image features and the depth of image points. For different points in a particular image, the determined relationship is used together with local and global image features including monocular cues to determine relative depths of the points.

Abstract: A machine may be configured to access an image of an item described by a description of the item. The machine may determine an image quality score of the image based on an analysis of the image. A request for search results that pertain to the description may be received by the machine, and the machine may present a search result that references the item's image, based on its image quality score. Also, the machine may access images of items and descriptions of items and generate a set of most frequent text tokens included in the item descriptions. The machine may identify an image feature exhibited by an item's image and determine that a text token from the corresponding item description matches one of the most frequent text tokens. A data structure may be generated by the machine to correlate the identified image feature with the text token.

Abstract: An apparatus and method for loading drums into a drum container, in which a function of gripping a lid of the drum container is added to a gripper used when a drum filled with radioactive waste is loaded into the drum container, thereby considerably reducing loading time of the drums, risk of dropping the drum, and preventing a radiation exposure risk. The apparatus includes a drum feeder transferring a drum, a drum container into which the drums transferred through the drum feeder are sequentially loaded, a support frame on which a lid of the drum container is placed when the drums are being loaded, and a crane having a gripper that selectively grips and transfers the drum or the drum container lid. The gripper includes radial gripper arms, an arm hydraulic unit reciprocating the gripper arms, jaws on inner sides of the gripper arms and gripping an outer surface of the drum, and latches for latching the drum container lid.