Vision Transformer
Cutting the Carbon Cost of Training: A New Tool Helps NLP Models Lower Their Gas Emissions
You can reduce your model’s carbon emissions by being choosy about when and where you train it.
Vision Transformer
Who Was That Masked Input? Pretraining Method Improves Computer Vision Performance
Researchers have shown that it’s possible to train a computer vision model effectively on around 66 percent of the pixels in each training image. New work used 25 percent, saving computation and boosting performance to boot.
Vision Transformer
Who Was That Masked Input? Pretraining Method Improves Computer Vision Performance
Researchers have shown that it’s possible to train a computer vision model effectively on around 66 percent of the pixels in each training image. New work used 25 percent, saving computation and boosting performance to boot.
Vision Transformer
Upgrade for Vision Transformers: Improved Efficiency for Vision Transformers
Vision Transformer and models like it use a lot of computation and memory when processing images. New work modifies these architectures to run more efficiently while adopting helpful properties from convolutions.
Vision Transformer
Upgrade for Vision Transformers: Improved Efficiency for Vision Transformers
Vision Transformer and models like it use a lot of computation and memory when processing images. New work modifies these architectures to run more efficiently while adopting helpful properties from convolutions.
Vision Transformer
Less Data for Vision Transformers: Boosting Vision Transformer Performance with Less Data
Vision Transformer (ViT) outperformed convolutional neural networks in image classification, but it required more training data. New work enabled ViT and its variants to outperform other architectures with less training data.
Vision Transformer
Less Data for Vision Transformers: Boosting Vision Transformer Performance with Less Data
Vision Transformer (ViT) outperformed convolutional neural networks in image classification, but it required more training data. New work enabled ViT and its variants to outperform other architectures with less training data.
Vision Transformer
High Accuracy at Low Power: An energy efficient method for computer vision
Equipment that relies on computer vision while unplugged — mobile phones, drones, satellites, autonomous cars — need power-efficient models. A new architecture set a record for accuracy per computation.
Vision Transformer
High Accuracy at Low Power: An energy efficient method for computer vision
Equipment that relies on computer vision while unplugged — mobile phones, drones, satellites, autonomous cars — need power-efficient models. A new architecture set a record for accuracy per computation.
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