This repository implements a multi-label image classification model using Keras and convolutional neural networks to identify natural scenes. The model uses binary crossentropy loss and sigmoid activation for multi-label output, with a probabilistic threshold method to convert predictions into binary labels. The implementation includes preprocessing pipelines, training scripts in Jupyter notebooks, and provides downloadable dataset and weight files.