کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

صفحه اصلی / هشتمین کنفرانس بین المللی کنترل ، ابزار دقیق و اتوماسیون

A New Fuzzy Logic Based Learning Rate Scheduling Method for Crop Classification With Convolutional Neural Network

نویسندگان :

Mohammad Hoseinzadeh¹ Javad Khoramdel² Yasamin Borhani³ Esmaeil Najafi⁴

1- دانشگاه صنعتی خواجه نصیرالدین طوسی 2- دانشگاه تربیت مدرس 3- دانشگاه صنعتی خواجه نصیرالدین طوسی 4- دانشگاه صنعتی خواجه نصیرالدین طوسی

کلمات کلیدی :

Deep Learning, CNN, Fuzzy Logic, Agriculture, Learning Rate Scheduler

چکیده :

Researchers have noticed the agriculture field due to its vital role in human lives. Convolutional neural networks, which are mostly used for image processing, can be used in agriculture applications to classify plants and plant diseases. In this paper, a fuzzy logic-based learning scheduler is proposed. This scheduler is compared to two famous schedulers Cosine Restart Decay and Exponential Decay on Agriculture crop classification dataset. Starting with the same initial random weights, a convolutional neural network trained with the fuzzy scheduler has reached a higher accuracy than the other methods.

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