| Budget Amount *help |
¥17,030,000 (Direct Cost: ¥13,100,000、Indirect Cost: ¥3,930,000)
Fiscal Year 2022: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2021: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2020: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2019: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2018: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
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| Outline of Final Research Achievements |
This study was conducted with the goal of making innovative advances in the use of deep learning for non-contact and non-destructive observations of vegetation. Deep learning techniques were developed and refined, and experiments were conducted to identify multiple target vegetation types. As a result, we were able to obtain good results in estimating the type and size of forest vegetation, as well as the distribution of invasive plants. The developed deep learning technique has potential for various applications in the future.
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