Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe

Spangle

https://doi.org/10.1007/978-94-017-1540-9r, most existing drowsiness detection methods do not consider the early stages of drowsiness or the practical feasibility of detection. To address this issue, we propose a gaze behavior pattern-based drowsiness detection model that effectively distinguishes early drowsiness. First, we extract the ga

廣大

ANTIC

Conclave

清楚

進(jìn)取心

Context Enhancement Methodology for Action Recognition in Still Images,prove feature representation. We performed a lot of experiments on the PASCAL VOC 2012 Action dataset and the Stanford 40 Actions dataset. The results demonstrate that our method performs effectively, with the state-of-the-arts outcomes being obtained on both datasets.

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現(xiàn)存

,Diversified Contrastive Learning For?Few-Shot Classification,s of all base class prototypes and conduct class-level contrastive learning between K-way class prototypes obtained from the current task and all base class prototypes. Meanwhile, we dynamically update all stored base class prototypes as the training progresses. We validate our model on mimiImagenet

FEAS

,Enhancing Cross-Lingual Few-Shot Named Entity Recognition by?Prompt-Guiding,nseen entity type information to the language model; 2) metric referents for predicting target language entity types; 3) a bridge between different languages that mitigates the language gap. Our experiments on several widely-used cross-lingual NER datasets (CoNLL, WikiAnn) in the few-shot setting de

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,FAIR: A Causal Framework for?Accurately Inferring Judgments Reversals,’s performance. In addition, we discuss the generalization ability of large language models for legal intelligence tasks using ChatGPT as an example. Our experiment has found that the generalization ability of large language models still has defects, and mining causal relationships can effectively i