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: A method for detecting an anchor-free object based on deep learning may include receiving a target image for object detection, inputting the image to a backbond network and performing learning to generate a heatmap, post-processing the heatmap, and outputting the post-processed result on a screen.

Abstract: An apparatus for recognizing an object using an image includes a depth map generator that generates a depth map using a feature map of the image based on a dilated convolutional neural network (DCNN) and an object recognition device that recognizes the object using the depth map generated by the depth map generator and the image.

Abstract: A method for detecting an anchor-free object based on deep learning may include receiving a target image for object detection, inputting the image to a backbond network and performing learning to generate a heatmap, post-processing the heatmap, and outputting the post-processed result on a screen.

Abstract: An apparatus for recognizing an object using an image includes a depth map generator that generates a depth map using a feature map of the image based on a dilated convolutional neural network (DCNN) and an object recognition device that recognizes the object using the depth map generated by the depth map generator and the 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: A beverage container has a body having an inlet which is formed so as to penetrate the bottom of a receiving unit. A holder is coupled to the inlet to open and close the inlet upon ascending or descending with a nozzle of a beverage supply device being inserted into the holder. A locking member is coupled to the ascending/descending wall of the holder to allow the holder to close the inlet. The locking member has a plurality of elastic arms for elastically supporting the holder.

Abstract: A beverage container has a body having an inlet which is formed so as to penetrate the bottom of a receiving unit. A holder is coupled to the inlet to open and close the inlet upon ascending or descending with a nozzle of a beverage supply device being inserted into the holder. A locking member is coupled to the ascending/descending wall of the holder to allow the holder to close the inlet. The locking member has a plurality of elastic arms for elastically supporting the holder.