In spoken conversation, people naturally take turns amid interjections and other patterns that aren’t strictly verbal. A new approach generated natural-sounding audio dialogs without training on text transcriptions that mark when one party should stop speaking and the other should chime in.
In spoken conversation, people naturally take turns amid interjections and other patterns that aren’t strictly verbal. A new approach generated natural-sounding audio dialogs without training on text transcriptions that mark when one party should stop speaking and the other should chime in.
Neural networks are making it possible to view parts of the Moon that are perpetually shrouded by darkness. Researchers devised a method called Hyper-effective Noise Removal U-net Software (HORUS) to remove noise from images of the Moon’s south pole.
Neural networks are making it possible to view parts of the Moon that are perpetually shrouded by darkness. Researchers devised a method called Hyper-effective Noise Removal U-net Software (HORUS) to remove noise from images of the Moon’s south pole.
Vision Transformers (ViTs) are overtaking convolutional neural networks (CNN) in many vision tasks, but procedures for training them are still tailored for CNNs. New research investigated how various training ingredients affect ViT performance.
Vision Transformers (ViTs) are overtaking convolutional neural networks (CNN) in many vision tasks, but procedures for training them are still tailored for CNNs. New research investigated how various training ingredients affect ViT performance.
Researchers at Baidu introduced PP-Matting, an architecture that, given an image, estimates the transparency of pixels surrounding foreground objects to create mattes without requiring additional input.
Researchers at Baidu introduced PP-Matting, an architecture that, given an image, estimates the transparency of pixels surrounding foreground objects to create mattes without requiring additional input.
Convolutional neural networks separate proteins into functional families without considering their shapes.
Convolutional neural networks separate proteins into functional families without considering their shapes.
Let’s get this out of the way: A brain is not a cluster of graphics processing units, and if it were, it would run software far more complex than the typical artificial neural network. Yet neural networks were inspired by the brain’s architecture.
Let’s get this out of the way: A brain is not a cluster of graphics processing units, and if it were, it would run software far more complex than the typical artificial neural network. Yet neural networks were inspired by the brain’s architecture.
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 (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.
People with certain genetic disorders share common facial features. Doctors are using computer vision to identify such syndromes in children so they can get early treatment.
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