{"id":20074194,"url":"https://github.com/furk4neg3/environment-image-classification","last_synced_at":"2026-01-20T04:01:41.743Z","repository":{"id":252581056,"uuid":"840849643","full_name":"furk4neg3/Environment-Image-Classification","owner":"furk4neg3","description":"Image classification model using intel image classification dataset. Created 6 models using various techniques, which involves CNN and fine-tuning. 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This involves images of scenes around the world. I've created 6 AI models for this problem. I've made data augmentation and preprocessing too.\n\n-\u003e First model is a baseline model which doesn't use deep learning.\n\n-\u003e Second model is a small dense model, which acts like baseline for deep learning models.\n\n-\u003e Third model is a small convolutional model, which only involves convolutional layers.\n\n-\u003e Fourth one is a bigger convolutional model, which involves max pooling layers.\n\n-\u003e Fifth one is the biggest of my self-created models, which is also a convolutional model. This one has more convolutional layers, pooling layers and involves batch normalization layers as well.\n\n-\u003e Last model uses fine-tuning, transfer-learning model is Inception v3 (I've created this model's v1 in TensorFlow, it's also in my GitHub).\n\n-\u003e Every model's loss and accuracies are visualized while training, and at the end they've been compared visually.\n\n-\u003e Best model which has 87% accuracy has been chosen, then I made a prediction with that model on a photo that my girlfriend sent me too, and it predicted the right label.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffurk4neg3%2Fenvironment-image-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffurk4neg3%2Fenvironment-image-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffurk4neg3%2Fenvironment-image-classification/lists"}