Abstract: The disclosure relates to an artificial intelligence (AI) system for mimicking functions, such as cognition and determination as of the human brain, by utilizing a machine learning algorithm such as deep learning, and an application thereof. Provided are a neural network learning method according to an AI system and applications thereof, the method including extracting, by using a masking filter having an effective value in a specific portion of the masking filter including weight information of at least one hidden layer included in a learning network model, characteristics of input data according to weight information of a filter corresponding to the specific portion, comparing output data with target data, the output data being obtained from the learning network model based on extracted characteristics of the input data, and updating a size of the specific portion having the effective value in the masking filter, based on a result of the comparing.

Abstract: The present disclosure provides a neural network training device for recognizing a class of an object included in an image based on an artificial intelligence (AI) system and an application thereof, the neural network training method including: acquiring, by using a first learning network model trained based on source training images respectively included in at least one class, feature information of a query image included in a class different from the at least one class; obtaining a generated image from the feature information of the query image by using a second learning network model acquiring feature information of the obtained generated image by using the first learning network model; and updating weights of layers respectively included in the first and second learning network models, based on a difference between the feature information of the query image and the feature information of the generated image and on a difference between the query image and the generated image.

Abstract: The present disclosure provides a neural network training device for recognizing a class of an object included in an image based on an artificial intelligence (AI) system and an application thereof, the neural network training method including: acquiring, by using a first learning network model trained based on source training images respectively included in at least one class, feature information of a query image included in a class different from the at least one class; obtaining a generated image from the feature information of the query image by using a second learning network model acquiring feature information of the obtained generated image by using the first learning network model; and updating weights of layers respectively included in the first and second learning network models, based on a difference between the feature information of the query image and the feature information of the generated image and on a difference between the query image and the generated image.

Abstract: The disclosure relates to an artificial intelligence (AI) system for mimicking functions, such as cognition and determination as of the human brain, by utilizing a machine learning algorithm such as deep learning, and an application thereof. Provided are a neural network learning method according to an AI system and applications thereof, the method including extracting, by using a masking filter having an effective value in a specific portion of the masking filter including weight information of at least one hidden layer included in a learning network model, characteristics of input data according to weight information of a filter corresponding to the specific portion, comparing output data with target data, the output data being obtained from the learning network model based on extracted characteristics of the input data, and updating a size of the specific portion having the effective value in the masking filter, based on a result of the comparing.

Abstract: Provided is an image surveillance method and apparatus. The image surveillance method includes photographing a predetermined place and generating an image signal corresponding to the predetermined place, detecting a change in the image signal by calculating a difference between a current frame and a previous frame of the generated image signal, and generating alarm information corresponding to the detected change in the image signal in order to alarm a user.

Abstract: An apparatus and a method of guiding a user along a travel path by using global positioning system (GPS) information are described. The method includes aligning images in a selected order based on a user input; extracting location information of the aligned images; setting a travel destination and a travel sequence based on the location information extracted from the aligned images; obtaining the user's location by using the global positioning system (GPS); and guiding the user along a travel path to the travel destination based on the user's location.

Abstract: An apparatus and a method of guiding a user along a travel path by using global positioning system (GPS) information are described. The method includes aligning images in a selected order based on a user input; extracting location information of the aligned images; setting a travel destination and a travel sequence based on the location information extracted from the aligned images; obtaining the user's location by using the global positioning system (GPS); and guiding the user along a travel path to the travel destination based on the user's location.

Abstract: Provided is an image processing method and apparatus for improving image quality and enhancing a three-dimensional effect. By extracting an interest feature index from an input image based on a depth sensation estimation cue existing in the image, calculating an interest feature index integration map based on the interest feature index and importance of interest of the depth sensation estimation cue, and performing discrimination processing of the image based on the interest feature index integration map, three-dimensional effect and true sensation enhancement processing can be performed based on the probability of the existence of a depth sensation estimation cue, without segmentation of an object of interest, correct depth information, or an object model.

Abstract: Provided is an image processing method and apparatus. The image processing method includes receiving an image signal an image, detecting a feature of the image, and analyzing the image signal based on the detected feature of the image, performing segmentation on the image signal according to the analysis result, and performing image processing on the image signal according to the segmentation result.

Abstract: An image analysis method, medium and apparatus for segmentation of a moving image, and a moving image segmentation system. The image analysis method includes receiving an image signal representing an image, detecting features of the image by calculating a difference between the current frame of the image signal and its previous frame, analyzing the image signal based on the detected features of the image, and performing segmentation on the image signal according to the analysis result, thereby separately performing segmentation on all types of moving images. In other words, by using an appropriate segmentation method according to a feature of an image, effective segmentation can be achieved.

Abstract: Provided are an image processing method and apparatus capable of improving the result of segmenting an image and discriminatively determining the extent of processing the image. In the method, the extent of segmentation of the image is calculated; the result of segmentation is compensated for and the extent of processing the image is determined, based on the calculated extent of segmentation; and each region of the image is discriminatively processed according to the determined extent of processing. Accordingly, it is possible to improve the precision of the result of segmentation and continuously control the extent of discriminative processing around a complex image object.

Abstract: Provided are an image processing method and apparatus capable of improving the result of segmenting an image and discriminatively determining the extent of processing the image. In the method, the extent of segmentation of the image is calculated; the result of segmentation is compensated for and the extent of processing the image is determined, based on the calculated extent of segmentation; and each region of the image is discriminatively processed according to the determined extent of processing. Accordingly, it is possible to improve the precision of the result of segmentation and continuously control the extent of discriminative processing around a complex image object.

Abstract: Provided is an image processing method and apparatus for improving image quality and enhancing a three-dimensional effect. By extracting an interest feature index from an input image based on a depth sensation estimation cue existing in the image, calculating an interest feature index integration map based on the interest feature index and importance of interest of the depth sensation estimation cue, and performing discrimination processing of the image based on the interest feature index integration map, three-dimensional effect and true sensation enhancement processing can be performed based on the probability of the existence of a depth sensation estimation cue, without segmentation of an object of interest, correct depth information, or an object model.

Abstract: Provided is an image processing method and apparatus. The image processing method includes receiving an image signal an image, detecting a feature of the image, and analyzing the image signal based on the detected feature of the image, performing segmentation on the image signal according to the analysis result, and performing image processing on the image signal according to the segmentation result.

Abstract: Provided is an image surveillance method and apparatus. The image surveillance method includes photographing a predetermined place and generating an image signal corresponding to the predetermined place, detecting a change in the image signal by calculating a difference between a current frame and a previous frame of the generated image signal, and generating alarm information corresponding to the detected change in the image signal in order to alarm a user.

Abstract: An image analysis method, medium and apparatus for segmentation of a moving image, and a moving image segmentation system. The image analysis method includes receiving an image signal representing an image, detecting features of the image by calculating a difference between the current frame of the image signal and its previous frame, analyzing the image signal based on the detected features of the image, and performing segmentation on the image signal according to the analysis result, thereby separately performing segmentation on all types of moving images. In other words, by using an appropriate segmentation method according to a feature of an image, effective segmentation can be achieved.