The classification of fashion cloth images is an important and challenging task in the field of computer vision. In recent years, deep learning (DL) techniques, especially Convolutional Neural ...

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 ...

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 ...

Breast cancer diagnosis, based on histopathological imaging, is essential for clinical decision-making due to complex nature of breast cancer subtypes, diverse morphological characteristics of lesions ...

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 ...

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_ ...

Images : How it works : classify.py is the main python file that trains the model to recognise different types of bears by learning from images We use a neural network (CNN) here to look at 50-100 ...

Therefore, classifying sensor data appropriately is essential for ensuring the reliability and efficiency of IIoT systems. In this paper, we propose the Shared-Encoder Transformer (SET) scheme for ...