Asmaa Abbas

Chest X-ray,Chest X-ray Images,Convolutional Neural Network,Image Classification,Pre-trained Convolutional Neural Network,Transfer Learning,Annotated Dataset,Classification Performance,Convolutional Neural Network Model,Deep Convolutional Neural Network,Image Dataset,ImageNet Pre-trained Model,Knowledge Transfer,Medical Imaging,Support Vector Machine,Training Set,AlexNet,COVID-19 Cases,COVID-19 Detection,Cancer Imaging,Case Detection,Challenging Problem,Class Composition,Colorectal Cancer,Colorectal Cancer Dataset,Computer-aided Diagnosis System,Convolutional Layers,Convolutional Network,Convolutional Neural Network Architecture,Data Augmentation,Deep Features,Deep Learning,Detection Accuracy,Diagnosis System,Feature Learning,Feature Maps,Fully-connected Layer,Gray Level Co-occurrence Matrix,Image Annotation,Image Classification Tasks,Image Recognition,ImageNet Pretraining,Interstitial Lung Disease,Large-scale Image,Large-scale Image Datasets,Learning Curve,Learning Models,Learning Rate,Lung Imaging,Lung Regions,