4M is a framework for training "any-to-any" foundation models, using tokenization and masking to scale to many diverse modalities. Models trained using 4M can perform a wide range of vision tasks, ...
Root Mean Square Error,Convolutional Neural Network,Feature Maps,Robotic System,Image Segmentation,Segmentation Accuracy,Adaptive Control,Attention Mechanism,Global Features,Local Features,Long ...
Point Cloud,Radio Frequency Signal,Bounding Box,Fast Fourier Transform,Feature Maps,Frequency Modulated Continuous Wave,Human Pose Estimation,Radar Data,Radar Signal ...
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