Deploy your Flask web app classifier on Heroku which is written using fastai library.
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Updated
Nov 19, 2019 - HTML
Deploy your Flask web app classifier on Heroku which is written using fastai library.
Demo of Face Recognition web service
Detect objects from a webcam in your browser with Cloudflare Workers AI!
We use pretrained networks VGGnet, AlexNet, GoogLeNet, ResNet which trained on the ImageNet dataset as a feature extractor to classify images.
Explainable Speaker Recognition system
Traffic sign classification using Resnet deep network
Image Style Recognition using Transfer Learning with Pre-trained ResNet
The system in this research uses transfer learning to categorise the many forms of weather. These weather conditions are primarily divided into 5 groups: cloudy, sunny, rainy, foggy, and sunrise. High-performance classifiers in artificial intelligence (AI) mostly use deep-learning (DL) techniques.
Cotton disease detection using CNN
Predict the apparent age of a person possibly in real time. The model used is pre-trained on VGG16 architecture and then trained using a convolutional neural network on the ChaLearn LAP dataset which consists of 8000 image samples. Test Accuracy achieved – 84%.
Easy and Useful ResNet Visualization Tool for AI Researchers and Developers
Project Website for the Deep Learning Online Seminar at University
A web-based animal classification system using Zero-Shot Learning and ResNet, built with Flask and PyTorch. This application can classify animals in images without being explicitly trained on them, using semantic embeddings to make predictions.
Dog breed classification using AWS SageMaker. This project fine-tunes a pre-trained ResNet model with transfer learning, applies hyperparameter tuning, and leverages SageMaker Debugger and Profiler for performance optimization. The trained model is deployed to a real-time endpoint to serve image predictions.
🐮 CUAI Deep Learning Study Materials (2020.01 - 2020.03) 🧠
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