5 accepted papers
Accurate prediction of typhoon tracks is essential for effective disaster prevention strategies. Given that typhoon tracks can be conceptualized as a special class of time series, promising results have been achieved via the learning transferability of large language models (LLMs) in time series for…
Recently, deep learning-based methods has gained increasing attention in typhoon tasks. Due to different optimization targets, existing works apply multi-object detection to typhoon detection and keypoint detection to typhoon eye location. However, such two-stage methods ignored the internal connect…
As a sub-task of visual grounding, linking people across text and images aims to localize target people in images with corresponding sentences. Existing approaches tend to capture superficial features of people (e.g., dress and location) that suffer from the incompleteness information across text an…
Forecasting rapid intensification (RI) of tropical cyclones (TC) is an important and challenging task. However, existing RI forecast methods pay little attention to the imbalanced distribution of RI with dynamic statistical models or ma-chine learning methods. Actually, RI prediction is a class-imba…
We propose a multi-scale approach to extract annotations from document images in a meaningful way. It compares the rectified captured image with original image, which can be obtained through image retrieval technology, at various resolutions, in order to remove the noise caused by nonuniform distort…