TOWARDS TRUSTWORTHY WILDFIRE DETECTION: INTEGRATING EXPLAINABILITY AND UNCERTAINTY IN DEEP LEARNING MODELS
Kalit so‘zlar:
trustworthy artificial intelligence; wildfire detection; Grad-CAM; uncertainty calibration; deep learning.Annotatsiya
Yongʻinlar iqlim oʻzgarishi taʼsirida yil davomida davom
etadigan tahdidga aylangan boʻlib, bu ularni erta aniqlashda chuqur
oʻrganishning ahamiyatini oshiradi. Maqolada CNN, ResNet-18 va DenseNet-121
modellarini Grad-CAM tushuntirish mexanizmi hamda Monte Carlo Dropout va
Temperature Scaling asosidagi noaniqlik bahosi bilan birlashtiruvchi
BlazeVeritas AI tizimi taqdim etiladi. Tizim FastAPI va Streamlit yordamida
ishlab chiqilgan. Natijalar tushuntiruvchanlik va noaniqlikni birga qoʻllash qaror
qabul qilish ishonchliligini oshirishini koʻrsatadi.
Manbalar
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