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Transfer learning of model alexnet for image classification to matlab(nanheekim)
- 1. Fire detector Term Project 11譟 蟾 蟠蠍一 豌讌
- 2. Introduction Main Conclusion - Topic - Motivation - Condition check - Creativity - Practicality - Demo video
- 3. - 襯 螳讌 語 覿覿 - CCTV, 谿 企 豺企 煙 覿殊 螳 - れ 伎
- 4. 1. 覿 貉れ蠍 覿蟒 語 覩碁Μ 谿 襦 2. 讌 蟆曙郁 れ 轟 覈襯企 蟆曙 3. 郁鍵 螳讌 覲企 蟆 螳( 讌 螳) 螳, 狩 蠏覈, 碁 狩 豕 覓伎語朱 覿蟒 覦蟆 螳
- 5. Condition check Condition 1: Use MATLAB
- 6. Condition check Condition 2: Input should be an image fire DB 140 from youtube 覿 讌螻 覿 讌 蟷 INPUT
- 7. Condition check Condition 3: Number of convolution layers 1 Condition 4: You should train your CNN using your DB or public DB ALEX NET
- 8. Condition check Condition 3: Number of convolution layers 1 Condition 4: You should train your CNN using your DB or public DB
- 9. Condition check Condition 3: Number of convolution layers 1 Condition 4: You should train your CNN using your DB or public DB 譴 企語 蠍郁 襷讌 牛 DB襯 覈 螳 伎襦 觸 RESIZE
- 10. Learning 蟆郁骸 れ螻 螳 覿 讌螻 覿 讌 覿襯企.
- 11. Learning 朱襖襷 讌れ 覿 讌襷 螻殊 启
- 13. Learning 启 ロ 覈
- 14. Detect 覿 讌 覦郁化朱覿 覿 detect
- 15. Detect 覲 伎
- 16. Detect ROI 2螳 伎 boxing ROI 讌 蟆豌 detect
- 17. Detect ROI 1螳 ROI 襷 讌襦 蟆郁骸
- 18. Solving Problem る 譴 螳 れ 覿覿 : window 蟯襴螳 蠍襦 ル伎 レ 蟠 り レ る襯 牛 願屋
- 19. Creativity & Practicality 1. DB襯 譯朱 れる 牛 覿 語. 2. 覈旧 覿 detect 螳ロ. 3. 碁 覈襯 蟆曙一 豐蠍 覦蟆 . 4. 企 螳り化覲企慨 蟆郁骸襯 豢 . 5. 螳 蟆暑慨 螻ル 蟆 誤 . 讌 螳. 螳, 狩 蠏覈, 碁 狩 豕
- 20. Demo video
- 21. : matlab 企 襷れ伎 蟆(ろ語, )れ 襷 螻, 伎譴 覃 譬 蟆郁骸襯 詞企 手 . 企 襷れ伎 蟆 覲伎 蟆 譬 蟆 螳. Conclusion
- 22. Thank you