KLASIFIKASI GAMBAR DATASET FASHION-MNIST MENGGUNAKAN DEEP CONVOLUTIONAL NEURAL NETWORK: Array

JiTEKH (Jurnal Ilmiah Teknologi Harapan)
Vol. 7 No. 1 (2019): Maret 2019

This study uses the Fashion-MNIST dataset from Zalando Research, which consists of 60000 images for training and 10000 images for testing, each image size 28x28 pixels. The deep learning method used is the Deep Convolutional Neural Network (DCNN), with the activation function relu on the inside of the layer and softmax at the end of the layer. Test accuracy without using dropout gets 92.69% with loss of 0.445 and using dropout gets 92.84%, loss 0.206.