Abstract: A cap logo applicator, and method of fabricating, includes a first mandrel having a front and a back, the first mandrel having a curved, non-cylindrical surface, and a relief space in the back such that when a cap is positioned on the first mandrel, a front of the cap is in contact with the non-cylindrical surface and a top of the cap extends over the relief space, and a second mandrel opposing the first mandrel and configured to apply pressure to the first mandrel. At least one of the first mandrel and the second mandrel includes a heater.

Abstract: A heat press includes a lower platen and an upper swing arm attached to a base, and an upper platen having a heater therein. The upper platen is coupled to the upper swing arm via a piston rod, and operable via a linkage. The linkage includes a coupler linked between the upper swing arm and a print handle and includes an input link that rotationally couples the print handle to the piston rod such that a motion of the print handle moves the piston rod up or down. The heat press includes a control housing that is electrically coupled to the heater. The upper swing arm is operable to swing the upper platen away from the lower platen when not in contact with the lower platen. The control housing remains in a stationary position regardless of a position of the upper swing arm.

Abstract: A method includes capturing images at a device and analyzing the images at the device using a first analysis model to obtain information regarding an observed object that corresponds to a predetermined object. The method also includes determining whether the information regarding the observed object is consistent with stored mapping information, and, in response to determining that the information regarding the observed object is not consistent with the stored mapping information, modifying the stored mapping information based on the observed object.

Abstract: A press includes an upper platen assembly having a first heating element, a lower platen assembly disposed beneath the upper platen assembly, the lower platen assembly having a second heating element, and a support head adapted to move the upper platen assembly between an open position and a closed position with respect to the lower platen assembly. The press further includes at least one heater controller operatively coupled to the first heating element and to the second heating element, and configured to separately apply power to the first heating element and to the second heating element.

Abstract: A press includes an upper platen assembly having a first heating element, a lower platen assembly disposed beneath the upper platen assembly, the lower platen assembly having a second heating element, and a support head adapted to move the upper platen assembly between an open position and a closed position with respect to the lower platen assembly. The press further includes at least one heater controller operatively coupled to the first heating element and to the second heating element, and configured to separately apply power to the first heating element and to the second heating element.

Abstract: A food recognition assistant system includes technologies to recognize foods and combinations of foods depicted in a digital picture of food. Some embodiments include technologies to estimate portion size and calories, and to estimate nutritional value of the foods. In some embodiments, data identifying recognized foods and related information are generated in an automated fashion without relying on human assistance to identify the foods. In some embodiments, the system includes technologies for achieving automatic food detection and recognition in a real-life setting with a cluttered background, without the images being taken in a controlled lab setting, and without requiring additional user input (such as user-defined bounding boxes). Some embodiments of the system include technologies for personalizing the food classification based on user-specific habits, location and/or other criteria.

Abstract: A food recognition assistant system includes technologies to recognize foods and combinations of foods depicted in a digital picture of food. Some embodiments include technologies to estimate portion size and calories, and to estimate nutritional value of the foods. In some embodiments, data identifying recognized foods and related information are generated in an automated fashion without relying on human assistance to identify the foods. In some embodiments, the system includes technologies for achieving automatic food detection and recognition in a real-life setting with a cluttered background, without the images being taken in a controlled lab setting, and without requiring additional user input (such as user-defined bounding boxes). Some embodiments of the system include technologies for personalizing the food classification based on user-specific habits, location and/or other criteria.

Abstract: A food recognition assistant system includes technologies to recognize foods and combinations of foods depicted in a digital picture of food. Some embodiments include technologies to estimate portion size and calories, and to estimate nutritional value of the foods. In some embodiments, data identifying recognized foods and related information are generated in an automated fashion without relying on human assistance to identify the foods. In some embodiments, the system includes technologies for achieving automatic food detection and recognition in a real-life setting with a cluttered background, without the images being taken in a controlled lab setting, and without requiring additional user input (such as user-defined bounding boxes). Some embodiments of the system include technologies for personalizing the food classification based on user-specific habits, location and/or other criteria.

Abstract: A food recognition assistant system includes technologies to recognize foods and combinations of foods depicted in a digital picture of food. Some embodiments include technologies to estimate portion size and calories, and to estimate nutritional value of the foods. In some embodiments, data identifying recognized foods and related information are generated in an automated fashion without relying on human assistance to identify the foods. In some embodiments, the system includes technologies for achieving automatic food detection and recognition in a real-life setting with a cluttered background, without the images being taken in a controlled lab setting, and without requiring additional user input (such as user-defined bounding boxes). Some embodiments of the system include technologies for personalizing the food classification based on user-specific habits, location and/or other criteria.