TensorFlow implementation of the Xception Model by François Chollet
-
Updated
Sep 9, 2019 - Python
TensorFlow implementation of the Xception Model by François Chollet
real-time face detection and emotion classification
Web App to identify Humans and extract Human Bodies from the image without Background
Online learning platform with automatic engagement recognition
Tagging images of bank cheques
Tagging images of bank cards, such as credit card, debit card, etc, based on Xception pretrained deep feature extraction and my own trained classification layers
Identification of Medicinal Plants Using Xception
Repositori untuk aplikasi Pencarian Kesamaan Gambar menggunakan Flask dan model CNN + Xception
Xception1d implementation for audio categorization
Workshop CDK Template to provision infra for the Deep Visual Search workshop
Dog Breed Classification with pre-trained xception model using feature extraction with convnet.
Tagging the images which have the road signs
A CNN using the architecture of the Xception model to build a multi-class garbage classifier.
Segmentation using DeepLabV3+
Food recognition base on its class and weight
A machine learning project for predicting customer churn, enabling businesses to identify at-risk customers and develop retention strategies.
Brain Tumor Classification project leveraging neural networks to classify MRI scans with high accuracy. Features include a Streamlit-based app for predictions, Gemini 1.5 Flash for interpretability, and advanced visualizations. It also includes model comparison, multimodal LLM integration, and real-time interactions.
Our custom AI Pipeline on Fundus disease for 2019 Konyang-hackathon.
ROS 2-based real-time emotion recognition with Coral Edge TPU, using a quantized Mini-XCEPTION model trained on FER-2013.
Add a description, image, and links to the xception-model topic page so that developers can more easily learn about it.
To associate your repository with the xception-model topic, visit your repo's landing page and select "manage topics."