Researchers demonstrate that misleading text in the real-world environment can hijack the decision-making of embodied AI systems without hacking their software. Self-driving cars, autonomous robots ...
Abstract: This paper proposes a multi-label text classification algorithm based on causal relationships to address the current challenge of accurately capturing label correlations in multi-label text ...
Abstract: The approach we offer makes use of CNN, attention methods and SVM to develop a combined framework that reaches higher performance. Attention mechanisms and CNN networks are used by this ...
Abstract: This paper proposes a novel hybrid classification model obtained by fusion of two Swarm Intelligence techniques (Bat Algorithms (BA) and Grey Wolf Optimizer (GWO)) with a Deep Convolutional ...
Abstract: Monitoring and staging of sleep are crucial for understanding physiological mechanisms, diagnosing diseases, and evaluating intervention outcomes. Currently, deep learning methods are widely ...
Abstract: Legal documents' length, complexity, and plenty of domain-specific language make classification and analysis of them challenging. Often lacking the required contextual depth, conventional ...
Abstract: The classic K-Nearest Neighbor (KNN) classification algorithm is widely used in text classification. This paper proposes an efficient algorithm for text classification by improving the ...
Trump allies text CNN host live, disputing 'reeling' headline after controversial interview with White House chief of staff Susie Wiles. Trump signs order to reclassify marijuana as Schedule III drug ...
Abstract: With the increasing demand for accurate classification of music content, the automatic classification technology of music style is particularly important in the fields of personalized music ...
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