As climate change and human activity increase the likelihood of devastating wildfires, the need for early fire detection methods is inevitable. Although, it has been shown that deep learning and artificial intelligence can offer a solution to this problem, there is still a lot of room for improvement. In this video, two new deep learning approaches to fire detection are developed and investigated utilizing pre-trained ResNet-50 and Xception for feature extraction with a detailed comparison against support vector machine (SVM), ResNet-50, Xception, and MobileViT architectures.