7/13/2023 0 Comments Pure pc computersBut before I explain the model, let’s first understand the working of an MLP. This article will explain how they achieve this. As this article will show, it’s impressive to see that this pure MLP architecture attains competitive scores compared to state-of-the-art models on image classification benchmarks. This paper by Google shows that neither CNNs nor self-attention modules are necessary to solve computer vision tasks. No CNNs, no self-attention mechanisms, only MLPs? A good example is the Vision Transformer.Ĭan we do away with both CNNs and attention mechanisms to only using Multi-Layer Perceptrons (MLPs) to solve computer vision problems in machine learning? But, over the last year, we’ve seen transformers with self-attention modules replacing CNNs. Convolutional Neural Networks (CNNs) have been used over the years to solve problems in computer vision.
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