Topic: "xception-net"
farhan1503001/Image-Forgery-Detection
Comparison between different DL models such as VGGnet,InceptionV3,Resnet for copy move forgery detection
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raghavm1/CZ4041--Machine-Learning
The project for NTU's course on Machine Learning, CZ4041
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anant1203/Applying-Deep-Learning-for-Large-scale-Quantification-of-Urban-Tree-Cover
To find out vegetation cover using deep learning model that can be deployed on the edge device. Dataset used to train the model is cityscape dataset. Model used are Unet and Mobile net V2 model.
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hrsht-13/PneumoniaDetection
Using an External dataset to get the pre-trained weights of the NIH dataset and training on the provided dataset to detect the presence of pneumonia.
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utkuatasoy/AI-Powered-Deepfake-Detection
The purpose of this project is to develop an AI-powered system capable of detecting deepfake facial data in biometric systems. By leveraging machine learning, specifically XceptionNet architecture, the project aims to classify facial data as real or fake with high accuracy and reliability.
Language: Jupyter Notebook - Size: 141 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 1 - Forks: 0
Aditya1Jhaveri/Cervical-Cancer-Image-Classification-in-Deep-Learning
This repository hosts the Cervical Cancer Image Classification project, a comprehensive effort aimed at improving the classification accuracy of Squamous Cell Carcinoma (SCC) through advanced deep learning models and ensemble techniques. The project utilizes the Herlev dataset.
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Afrid1045/Brain-Tumor-Severity-Prediction-using-Multi-Modal-Squeeze-and-Excitation-Network
The project focuses on classifying brain tumors using the Multi-Modal Squeeze and Excitation Network.
Language: Jupyter Notebook - Size: 4.16 MB - Last synced at: 26 days ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0
avd1729/Xception
Flower image classification using Transfer learning (Xception)
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parham1998/CNN_Image_Annotaion
Implementation of some basic Image Annotation methods (using various loss functions & threshold optimization) on Corel-5k dataset with PyTorch library
Language: Python - Size: 152 KB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
farhan1503001/Breast-Cancer-Classification-From-Histopathological-Images
Improved Deep Learning Model has been used to classify Breast Cancer from Histopathological Tissue Images.
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achraf-oujjir/xception-on-ham10k
In this project, we used a transfer learning approach to build an image classification model for the classification of skin lesion, we trained our model specifically on the ham10000 dataset available on kaggle and we were able to achieve a 93.6% accuracy
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Pranav-Nagpure/Dog-Breed-Prediction-NB
IPython Notebook to build the model for Dog Breed Prediction
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Venn1998/GlaucomaDetection
Development and analysis of various deep NN models to detect glaucoma cases from fundus images. The performance of the best model was evaluated with cross-validation. Mean F1-score: 0.95975, with a standard deviation of 0.02274.
Language: Jupyter Notebook - Size: 6.62 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
