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Di Liu, Qiang Li, Sen Li, Jun Kong and Miao Qi
Pedestrian trajectory prediction is an important task in practical applications such as automatic driving and surveillance systems. It is challenging to effectively model social interactions among pedestrians and capture temporal dependencies. Previous m...
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Sebastian C. Ibañez and Christopher P. Monterola
Accurate prediction of crop production is essential in effectively managing the food security and economic resilience of agricultural countries. This study evaluates the performance of statistical and machine learning-based methods for large-scale crop p...
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Yingjie Du and Ning Ding
Crime is always one of the most important social problems, and it poses a great threat to public security and people. Accurate crime prediction can help the government, police, and citizens to carry out effective crime prevention measures. In this paper,...
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Panagiotis Skondras, Panagiotis Zervas and Giannis Tzimas
In this article, we investigate the potential of synthetic resumes as a means for the rapid generation of training data and their effectiveness in data augmentation, especially in categories marked by sparse samples. The widespread implementation of mach...
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Hongmei Zhang and Shuiqing Wang
The analysis of thin sections for lithology identification is a staple technique in geology. Although recent strides in deep learning have catalyzed the development of models for thin section recognition leveraging varied deep neural networks, there rema...
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Sicong Liu, Qingcheng Fan, Shanghao Liu and Chunjiang Zhao
Animal pose estimation has important value in both theoretical research and practical applications, such as zoology and wildlife conservation. A simple but effective high-resolution Transformer model for animal pose estimation called DepthFormer is provi...
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