Titlebook: Artificial Intelligence XXXVIII; 41st SGAI Internatio Max Bramer,Richard Ellis Conference proceedings 2021 Springer Nature Switzerland AG 2

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书目名称Artificial Intelligence XXXVIII影响因子(影响力)




书目名称Artificial Intelligence XXXVIII影响因子(影响力)学科排名




书目名称Artificial Intelligence XXXVIII网络公开度




书目名称Artificial Intelligence XXXVIII网络公开度学科排名




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书目名称Artificial Intelligence XXXVIII被引频次学科排名




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书目名称Artificial Intelligence XXXVIII年度引用学科排名




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书目名称Artificial Intelligence XXXVIII读者反馈学科排名

Obedient

Generation of Human-Aware Navigation Maps Using Graph Neural Networks tasks. The results outperform similar state-of-the-art-methods considering the accuracy for the dataset and the navigation metrics used. The applications of the proposed framework are not limited to human-aware navigation, it could be applied to other fields where cost map generation is needed.

Vulnerary

虚弱的神经

AI Methods of Autonomous Geological Target Selection in the Hunt for Signs of Extraterrestrial Lifee extracted texture information to a rotationally invariant form. The highest accuracy in positive rock type identification was 85% which was achieved by using a weighted binarization of the texture features to perform a circular shift on the feature vector.

Bravura

Named Entity Recognition and Relation Extraction for COVID-19: Explainable Active Learning with Wordord2vec models with additional examples of use from the biomedical literature. We propose interpreting the NER and REX tasks for COVID-19 as Question Answering (QA) incorporating general medical knowledge within the question, e.g. “does ‘cough’ (n-gram) belong to ‘clinical presentation/symptoms’ for

外貌

除草剂

Exploring Place in the Australian Landscapeultiple controls and statistical analysis, we find clear evidence that fine-tuned commonsense language models still do not generalize well, even with moderate changes to the experimental setup, and may, in fact, be susceptible to dataset bias.

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催眠药

Impact of platforms on urban space,namics model. However, it is challenging to achieve good accuracy on dynamics models for highly complex domains due to stochasticity and compounding noise in the system. A majority of model-based RL focuses on dynamics models that derive policies from observation space. Deriving policies from observ

Assemble