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With relative position bias, you are extending the concept of self-attention to also encode the distance between any two tokens. Basically you let the model itself learn the relative distance between any 2 tokens instead of feeding that information yourself. Most of the time (as shown in the paper), the model does a good job at figuring out the relationships ...


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The reason for this seems to be your are importing from tensorflow.keras.layers import * But while your are calling you are using : layers.Input(shape=(IMG_SIZE, IMG_SIZE, 3)) this calling will give you an error so instead try below import Please try this import : from tensorflow.keras import layers


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I think, you are trying to link a particular analysis logic to model architecture, however this is not how this not how cnn and most DL models work. The logic behind decreasing the filter size or the network dimensionality as a general rule, is the "distillation" of characteristics that differentiate classes. In other words a representation of ...


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COCO dataset contains more than 91 stuff categories with 330K images (>200K labeled). Perhaps it is not the best way to identify people using YOLOv5 because your workshop has illumination changes during the daytime (natural light and lamps?). Thus, I suggest the following: Use other pre-trained weights for people detection only, use this. I got them from ...


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Models can be benchmarked by absolute values or relative values. Absolute values are frequently used in a business context. Is the model good enough to accomplish a useful task? Relative values are often used for comparing different models and/or different hyperparameters. One of the primary goals of machine learning is prediction. The best way to assess ...


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