  Accurate waste disposal, at the point of disposal, is crucial to fighting
climate change. When materials that could be recycled or composted get diverted
into landfills, they cause the emission of potent greenhouse gases such as
methane. Current attempts to reduce erroneous waste disposal are expensive,
inaccurate, and confusing. In this work, we propose DeepWaste, an easy-to-use
mobile app, that utilizes highly optimized deep learning techniques to provide
users instantaneous waste classification into trash, recycling, and compost. We
experiment with several convolution neural network architectures to detect and
classify waste items. Our best model, a deep learning residual neural network
with 50 layers, achieves an average precision of 0.881 on the test set. We
demonstrate the performance and efficiency of our app on a set of real-world
images.
