| Budget Amount *help |
¥59,410,000 (Direct Cost: ¥45,700,000、Indirect Cost: ¥13,710,000)
Fiscal Year 2019: ¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000)
Fiscal Year 2018: ¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000)
Fiscal Year 2017: ¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000)
Fiscal Year 2016: ¥11,570,000 (Direct Cost: ¥8,900,000、Indirect Cost: ¥2,670,000)
Fiscal Year 2015: ¥13,130,000 (Direct Cost: ¥10,100,000、Indirect Cost: ¥3,030,000)
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| Outline of Final Research Achievements |
We have obtained step-by-step achievements towards realizing an AI that can recognize the Shitsukan of an object from its single image. We have developed the following methods: i) a CNN-based method for Shitsukan recognition based on learning to rank image pairs; ii) a method for mining visually recognizable Shitsukan concepts from pairs of images and their descriptions on the Web; iii) a method for generating appropriate titles for images of products while capturing the context-aware Shitsukan concepts. The developments of the above lead to the conclusion that Shitsukan recognition is "comprehensive image recognition," and we successfully developed a network with an attention mechanism, which is an offshoot of today's multimodal deep neural networks for image understanding.
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