Hands-on Vision Transformers with PyTorch - Analytics India Magazine

With the rise in popularity of image and video analytics, the need for better and improved Convolution Neural Networks(CNNs) has been researched and implemented in industry to outperform several computer vision algorithms. We are moving towards an era of quantum computing and solving all the challenges related to the need for large computing power soon. Currently, all the vision tasks are trained on high-end GPUs/ TPUs and a massive amount of datasets. Transformers(Vaswani et al.), architecture was introduced in 2017, which uses self-attention to accelerate the training process. It was primarily created to solve some of the core challenges in Natural language processing(NLP) related tasks.