From 7d9149bfe416ac4ced551c905ef4b8be70ef4ae1 Mon Sep 17 00:00:00 2001 From: Anjana Tiha Date: Fri, 29 Mar 2019 17:15:35 -0400 Subject: [PATCH] Update README.md --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index c1e148e..eb4a423 100644 --- a/README.md +++ b/README.md @@ -2,15 +2,15 @@ 
 Domain             : Computer Vision, Machine Learning
 Sub-Domain         : Deep Learning, Image Recognition
-Techniques         : Deep Convolutional Neural Network, Transfer Learning, ImageNet, Auto ML, NASNetMobile
+Techniques         : Deep Convolutional Neural Network, Transfer Learning, ImageNet, NASNetMobile
 Application        : Image Recognition, Image Classification, Medical Imaging
### Description 
-1. Detected Malaria from microscopic tissue images with Auto ML (Google's "NASNet").
-2. For training, concatenated global pooling (max, average), dropout and dense layers to the output layer for final output prediction.
-3. Attained validation accuracy of 95.72% and loss 0.1385 on 27K+ (330MB+) image cancer dataset.
+1. Detected Malaria from microscopic tissue images by completely retraining pretrained model (Google's "NASNet") from scratch.
+2. For training, concatenated global max pooling, global average pooling, flattened output, then added a dense layer with batch normalization and dropout and give to the output layer for final output prediction.
+3. Attained validation accuracy of 95.72% and loss 0.1385 on 27K+ (330MB+) image malaria dataset.
#### Code