The transformer-based structure has an advantage in extracting global features and can make up for this deficiency. This paper proposes a hybrid multi-scale network model based on CNN and Swin ...

AdaBoost approaches have been used for multi-class imbalance classification with an imbalance ratio measured on class sizes. However, such ratio would assign each training sample of the same class ...

News text classification is crucial for efficient information acquisition and dissemination. While deep learning models, such as BERT and BiGRU, excel in accuracy for text classification, their high ...

In this research work, a convolutional neural network (CNN) model is proposed for multi-class classification problems with the efficient use of memory consumption. The proposed model has been ...

Online product reviews provide valuable insights into customer sentiment toward products; however, they often contain multiple sentences with redundant and non-essential content, making it harder to ...

As one of the fundamental tasks in aerial image understanding, multi-label aerial image scene classification attracts increasing research interest. In general, the semantic category of a scene is ...

On a hardware-software platform, the implementation of multi-class vehicle classification demonstrated its effectiveness. Within the realm of multi-class vehicle classification applications, the ...

Auroral image classification has long been a focus of research in auroral physics. However, current methods for automatic auroral classification typically assume that only one type of aurora is ...

New issue New issue Open Open DISABLED MULTIPLE There are multiple flaky tests in test_nn.py #157070 Labels aggregate flaky test issuemodule: flaky-testsProblem is a flaky test in CImodule: nnRelated ...

There are multiple flaky tests in test_transformers.py. Please investigate and fix the flakiness. disable the following tests: test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_ ...