Utilizing ResNet152V2 for Traffic Sign Classification: Achieve High Accuracy in Identifying 52 Sign Types with 99% Precision
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Updated
Apr 11, 2024 - Jupyter Notebook
Utilizing ResNet152V2 for Traffic Sign Classification: Achieve High Accuracy in Identifying 52 Sign Types with 99% Precision
Eye Disease Detection using Transfer Learning (DenseNet-121, EfficientNetB3, VGG-16, Resnet-152)
Brain Tumor MRI images have been classified into 4 classes by using Transfer Learning Models.
Klasifikasi Kanker otak dengan 7 model CNN
This notebook has the model created to predict COVID-19 only based on X-ray chest scans.
'CNN_Sorghum_Weed_Classifier' is an artificial intelligence (AI) based software that can differentiate a sorghum sampling image from its associated weeds images.
An End-to-End Pneumonia Diagnosis(from Chest X-Ray images) application built using Flask and Deep Learning models trained using TensorFlow on a Kaggle Dataset.
This project is a Steel Defect Detection System using a ResNet152V2-based deep learning model. The model predicts bounding boxes for steel defects in images and classifies them into multiple defect types. It is implemented using TensorFlow and Keras for the deep learning components.
Image classification
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