Multi-label image classification extends the traditional single-label paradigm by assigning multiple simultaneous labels to each image, reflecting the complexity of real-world scenes. This task poses ...
Abstract: Multi-label image classification needs to recognize multiple co-existing and semantically correlated labels within a single image. Existing Transformer-based methods employ label queries for ...
Abstract: Long-tailed image classification faces challenges of data imbalance and poor feature representation for tail classes, leading to biased predictions favoring head classes. While most existing ...
This tutorials is part of a three-part series: * `NLP From Scratch: Classifying Names with a Character-Level RNN <https://pytorch.org/tutorials/intermediate/char_rnn ...
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