Synthetic cannabinoids, a class of new psychoactive substances, have emerged as a significant public health and social stability threat due to their structural diversity, rapid iteration, and stronger ...

Given the complexity of multi-label tasks and the high cost of annotations, there is a need for active learning techniques tailored to deep multi-label classification. Active learning enables a model ...

Traditional methods of multi-label text classification, particularly deep learning, have achieved remarkable results. However, most of these methods use word2vec technology to represent sequential ...

Deep learning is increasingly being applied for the detection of clinically important features in the images beyond what can be perceived by the naked human eye. Chest X-ray images are one of the most ...

Researchers leverage new machine learning methods to learn from noisy labels for image classification October 12, 2022 by Zhuowei Wang ...

NeuralClassifier is designed for quick implementation of neural models for hierarchical multi-label classification task, which is more challenging and common in real-world scenarios. A salient feature ...

Keywords: multi-functional enzyme, function prediction, EC number, deep learning, hierarchical classification, multi-label learning Citation: Zou Z, Tian S, Gao X and Li Y (2019) mlDEEPre: ...