Abstract: The information processing apparatus according to the present disclosure synthesizes a handwriting image with a noise image to generate a synthesized image, generates a correct label indicative of handwriting pixels from the handwriting image, and applies the synthesized image and the correct label as learning data to generate a learning model.

Abstract: An image processing system performs tilt correction with respect to a document image having handwritten characters and typed letters mixed with each other. The image processing system separates the document image into an image with handwritten characters determined as handwritten characters and an image without handwritten characters not determined as handwritten characters, estimates a tilt angle of the image without handwritten characters, and corrects the document image on the basis of the tilt angle.

Abstract: An image processing system which corrects a text obtained by optical character recognition (OCR) using a neural network which has performed learning based on a falsely recognized portion of OCR and a text near the falsely recognized portion is provided. The image processing system acquires a neural network model which has been trained based on learning data in which first text information included in print data and second text information acquired by performing optical character recognition (OCR) processing on an image that is based on the print data are associated with each other, acquires an image obtained by a scanner, acquires third text information which is generated by performing OCR processing on the image obtained by the scanner, and outputs fourth text information according to inputting of the third text information based on the neural network model.

Abstract: An image processing system which corrects a text obtained by optical character recognition (OCR) using a neural network which has performed learning based on a falsely recognized portion of OCR and a text near the falsely recognized portion is provided. The image processing system acquires a neural network model which has been trained based on learning data in which first text information included in print data and second text information acquired by performing optical character recognition (OCR) processing on an image that is based on the print data are associated with each other, acquires an image obtained by a scanner, acquires third text information which is generated by performing OCR processing on the image obtained by the scanner, and outputs fourth text information according to inputting of the third text information based on the neural network model.

Abstract: Provided are a method and a device for efficiently decomposing gas hydrate pellets and extracting gas. That is, provided is a method for decomposing gas hydrate characterized by supplying gas hydrate pellets to a decomposition vessel, damming and gathering densely the pellets on a downstream side in the decomposition vessel, and passing hot water through this pellet layer which is in a densely gathered state, to thereby decompose the pellets into water and gas.

Abstract: Provided are a method and a device for efficiently decomposing gas hydrate pellets and extracting gas. That is, provided is a method for decomposing gas hydrate characterized by supplying gas hydrate pellets to a decomposition vessel, damming and gathering densely the pellets on a downstream side in the decomposition vessel, and passing hot water through this pellet layer which is in a densely gathered state, to thereby decompose the pellets into water and gas.