Abstract: The present disclosure relates to an interior material for a vehicle and a method for molding the interior material for the vehicle, and more specifically the method for molding an interior material for a vehicle according to the present disclosure includes heating a skin inserted into an upper end heater and a lower end heater spaced apart from each other; preforming the heated skin using an upper mold having a mold temperature set to have a set shape and a lower mold having a second mold temperature; and pressing the preformed skin and a core using a 1-1 mold and a 1-2 mold having set mold temperatures.

Abstract: A convolutional neural network (CNN) processing method includes selecting a survival network in a precision convolutional network based on a result of performing a high speed convolution operation between an input and a kernel using a high speed convolutional network, and performing a precision convolution operation between the input and the kernel using the survival network.

Abstract: A processor-implemented liveness test method includes detecting a face region in a query image, the query image including a test object for a liveness test, determining a liveness test condition to be applied to the test object among at least one liveness test condition for at least one registered user registered in a registration database, determining at least one test region in the query image based on the detected face region and the determined liveness test condition, obtaining feature data of the test object from image data of the determined at least one test region using a neural network-based feature extractor, and determining a result of the liveness test based on the obtained feature data and registered feature data registered in the registration database and corresponding to the determined liveness test condition.

Abstract: Disclosed is a target tracking method and apparatus. The target tracking apparatus includes a processor configured to obtain a first depth feature from a target region image and obtain a second depth feature from a search region image, obtain a global response diagram between the first depth feature and the second depth feature, acquire temporary bounding box information based on the global response diagram, updated the second depth feature based on the temporary bounding box information, obtain local feature blocks based on the first depth feature, obtain a local response diagram based on the local feature blocks and the updated second depth feature, and determine output bounding box information based on the local response diagram.

Abstract: A convolutional neural network (CNN) processing method includes selecting a survival network in a precision convolutional network based on a result of performing a high speed convolution operation between an input and a kernel using a high speed convolutional network, and performing a precision convolution operation between the input and the kernel using the survival network.

Abstract: A phase-change random access memory (PRAM) device includes a plurality of banks, a plurality of column redundancy cell arrays, and a plurality of column redundancy write drivers. Each of the plurality of column redundancy cell arrays corresponds to at least one of the banks. Each of the plurality of column redundancy write drivers corresponds to at least one of the column redundancy cell arrays. The column redundancy write drivers are configured to transmit respective redundancy test data to the corresponding ones of the column redundancy cell arrays in response to a test control signal, which may be activated in response to each program pulse for writing data. Related test and access methods are also discussed.

Abstract: A PRAM includes a memory cell array of phase change memory cells, and a write circuit receiving an externally provided first voltage and supplying a write pulse for writing data to the memory cells in a normal operation mode. The write circuit also receives an externally provided second voltage higher than the first voltage and supplies a firing pulse to at least one firing-failed phase change memory cell.

Abstract: Provided is a method of testing a phase change random access memory (PRAM). The method may include providing a plurality of PRAM cells each coupled between each of a plurality of first lines and each of a plurality of second lines intersecting the first lines, selecting at least one of the plurality of first lines while deselecting the remaining first lines and the plurality of second lines, pre-charging the selected at least one of the plurality of first lines to a predetermined or given voltage level, and sensing a change in the voltage level of the selected first line while supplying a monitoring voltage to the selected first line.

Abstract: A phase-change random access memory (PRAM) device includes a plurality of banks, a plurality of column redundancy cell arrays, and a plurality of column redundancy write drivers. Each of the plurality of column redundancy cell arrays corresponds to at least one of the banks. Each of the plurality of column redundancy write drivers corresponds to at least one of the column redundancy cell arrays. The column redundancy write drivers are configured to transmit respective redundancy test data to the corresponding ones of the column redundancy cell arrays in response to a test control signal, which may be activated in response to each program pulse for writing data. Related test and access methods are also discussed.

Abstract: A PRAM includes a memory cell array of phase change memory cells, and a write circuit receiving an externally provided first voltage and supplying a write pulse for writing data to the memory cells in a normal operation mode. The write circuit also receives an externally provided second voltage higher than the first voltage and supplies a firing pulse to at least one firing-failed phase change memory cell.

Abstract: Provided is a method of testing a phase change random access memory (PRAM). The method may include providing a plurality of PRAM cells each coupled between each of a plurality of first lines and each of a plurality of second lines intersecting the first lines, selecting at least one of the plurality of first lines while deselecting the remaining first lines and the plurality of second lines, pre-charging the selected at least one of the plurality of first lines to a predetermined or given voltage level, and sensing a change in the voltage level of the selected first line while supplying a monitoring voltage to the selected first line.