no code implementations • 11 Nov 2023 • Yingjie Niu, Ming Ding, Keisuke Fujii, Kento Ohtani, Alexander Carballo, Kazuya Takeda
The DRUformer is a transformer-based multi-modal important object detection model that takes into account the relationships between all the participants in the driving scenario.
no code implementations • 18 Jul 2023 • Yingjie Niu, Ming Ding, Maoning Ge, Robin Karlsson, Yuxiao Zhang, Kazuya Takeda
Our method aims to improve trust in classification results and empower users to gain a deeper understanding of the model for downstream tasks by providing visualizations of class-specific maps.
1 code implementation • 14 May 2023 • Yingjie Niu, Linyi Yang, Ruihai Dong, Yue Zhang
Our method has been theoretically and empirically shown to be effective in enhancing the generalization ability of both generative and discriminative models.
no code implementations • 29 Nov 2021 • Valerio Antonini, Yingjie Niu, Manuela Nayantara Jeyaraj, Sonal Santosh Baberwal, Faithful Chiagoziem Onwuegbuche, Robert Foskin
With the outbreak of COVID-19 pandemic, a dire need to effectively identify the individuals who may have come in close-contact to others who have been infected with COVID-19 has risen.