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AssigneeFujitsu Limited
InventorsTakuya Fukagai, Kyosuke Maeda, Koichi Shirahata, Yasumoto Tomita
Estimating the term…
An image recognition apparatus includes a processor including a plurality of arithmetic units; and a memory storing a plurality of data elements, each corresponding to one of candidate regions detected in an image and indicating a location and an evaluation value of the corresponding candidate region. The processor sorts the data elements by calculating in parallel, in reference to evaluation values, indexes each indicating a position of a corresponding one of the data elements in a sorted ordering and transferring in parallel, after the calculation of the indexes, the data elements based on the indexes. The processor selects part of the candidate regions based on the sorted ordering of the data elements.
An image recognition apparatus comprising:
An image recognition method comprising:
A non-transitory computer-readable recording medium storing therein a computer program that causes a computer to execute a process comprising:
Dependencies are inferred from the claim text.
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With interaction between the filter responses, e.g. cortical complex cells: integrating the filters into a hierarchical structure, e.g.…
General purpose image data processing: processor architectures; Processor configuration, e.g. pipelining
General purpose image data processing: memory management
Image analysis: determining position or orientation of objects or cameras
About 13 years 1 month of term left · ends 3 Dec 2039 (estimated)
This application is based upon and claims the benefit of priority of the prior Japanese Patent Application No. 2018-161464, filed on Aug. 30, 2018, the entire contents of which are incorporated herein by reference.
The embodiments discussed herein are related to an apparatus and method for image recognition.
There are known image recognition techniques for detecting the locations and classes of individual objects in an input image. Some image recognition techniques employ neural networks, such as pre-trained convolutional neural networks (CNNs). For example, region-based convolutional neural network (R-CNN) and fast R-CNN methods have been proposed.
FIG. 1 illustrates an exemplary image recognition apparatus according to a first embodiment;
FIG. 2 is a block diagram illustrating exemplary hardware of an image recognition apparatus;
FIG. 3 is a block diagram illustrating exemplary hardware of a GPU;
Several embodiments will be described below with reference to the accompanying drawings.
This part of the description explains a first embodiment.
FIG. 1 illustrates an exemplary image recognition apparatus according to the first embodiment.