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https://github.com/invictus717/MetaTransformer 变压器在多模态学习中的潜力和可扩展性。我们利用变压器的优势来处理长度变化的序列。然后,我们按照元方案提出数据到序列标记化,然后将其应用于 12 种模态,包括文本、图像、点云、音频、视频、红外、高光谱、X 射线、表格、图形、时间序列和惯性测量单元 (IMU) 数据。 12 modalities including text, image, point cloud, audio, video, infrared, hyper-spectral, X-Ray, tabular, graph, time-series, and Inertial Measurement Unit (IMU) data.
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https://github.com/invictus717/MetaTransformer
变压器在多模态学习中的潜力和可扩展性。我们利用变压器的优势来处理长度变化的序列。然后,我们按照元方案提出数据到序列标记化,然后将其应用于 12 种模态,包括文本、图像、点云、音频、视频、红外、高光谱、X 射线、表格、图形、时间序列和惯性测量单元 (IMU) 数据。
12 modalities including text, image, point cloud, audio, video, infrared, hyper-spectral, X-Ray, tabular, graph, time-series, and Inertial Measurement Unit (IMU) data.
The text was updated successfully, but these errors were encountered: