Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception

Kavli Affiliate: Feng Yuan | First 5 Authors: Yaxin Feng, Yuan Lan, Luchan Zhang, Guoqing Liu, Yang Xiang | Summary: Urban segmentation and lane detection are two important tasks for traffic scene perception. Accuracy and fast inference speed of visual perception are crucial for autonomous driving safety. Fine and complex geometric objects are the most […]


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Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception

Kavli Affiliate: Feng Yuan | First 5 Authors: Yaxin Feng, Yuan Lan, Luchan Zhang, Guoqing Liu, Yang Xiang | Summary: Urban segmentation and lane detection are two important tasks for traffic scene perception. Accuracy and fast inference speed of visual perception are crucial for autonomous driving safety. Fine and complex geometric objects are the most […]


Continue.. Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception

Prospects for detecting neutron star-white dwarf mergers with decihertz gravitational-wave observatories

Kavli Affiliate: Lijing Shao | First 5 Authors: Yacheng Kang, Chang Liu, Jin-Ping Zhu, Yong Gao, Lijing Shao | Summary: Based on different neutron star-white dwarf (NS-WD) population models, we investigate the prospects of gravitational-wave (GW) detections for NS-WD mergers, with the help of early warnings from two space-borne decihertz GW observatories, DO-Optimal and DECIGO. […]


Continue.. Prospects for detecting neutron star-white dwarf mergers with decihertz gravitational-wave observatories

Prospects for detecting neutron star-white dwarf mergers with decihertz gravitational-wave observatories

Kavli Affiliate: Lijing Shao | First 5 Authors: Yacheng Kang, Chang Liu, Jin-Ping Zhu, Yong Gao, Lijing Shao | Summary: Based on different neutron star-white dwarf (NS-WD) population models, we investigate the prospects of gravitational-wave (GW) detections for NS-WD mergers, with the help of early warnings from two space-borne decihertz GW observatories, DO-Optimal and DECIGO. […]


Continue.. Prospects for detecting neutron star-white dwarf mergers with decihertz gravitational-wave observatories

nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance

Kavli Affiliate: Jing Wang | First 5 Authors: Yunxiang Li, Bowen Jing, Xiang Feng, Zihan Li, Yongbo He | Summary: The recent developments of foundation models in computer vision, especially the Segment Anything Model (SAM), allow scalable and domain-agnostic image segmentation to serve as a general-purpose segmentation tool. In parallel, the field of medical image […]


Continue.. nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance

nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance

Kavli Affiliate: Jing Wang | First 5 Authors: Yunxiang Li, Bowen Jing, Zihan Li, Jing Wang, You Zhang | Summary: Automatic segmentation of medical images is crucial in modern clinical workflows. The Segment Anything Model (SAM) has emerged as a versatile tool for image segmentation without specific domain training, but it requires human prompts and […]


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Synthetic Speech Detection Based on Temporal Consistency and Distribution of Speaker Features

Kavli Affiliate: Zhuo Li | First 5 Authors: Yuxiang Zhang, Zhuo Li, Jingze Lu, Wenchao Wang, Pengyuan Zhang | Summary: Current synthetic speech detection (SSD) methods perform well on certain datasets but still face issues of robustness and interpretability. A possible reason is that these methods do not analyze the deficiencies of synthetic speech. In […]


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Image of Kerr-de Sitter black holes: An additional avenue for testing the cosmological constant

Kavli Affiliate: Ke Wang | First 5 Authors: Ke Wang, Chao-Jun Feng, Towe Wang, , | Summary: To explore the feasibility of utilizing black hole images to test the cosmological constant, we have developed a comprehensive analytical method for simulating images of Kerr-de Sitter black holes illuminated by equatorial thin accretion disks. Our findings indicate […]


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Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Kavli Affiliate: Zhuo Li | First 5 Authors: Mouxiang Chen, Chenghao Liu, Zemin Liu, Zhuo Li, Jianling Sun | Summary: The application of Unbiased Learning to Rank (ULTR) is widespread in modern systems for training unbiased ranking models from biased click logs. The key is to explicitly model a generation process for user behavior and […]


Continue.. Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank

Kavli Affiliate: Zhuo Li | First 5 Authors: Mouxiang Chen, Chenghao Liu, Zemin Liu, Zhuo Li, Jianling Sun | Summary: Unbiased Learning to Rank (ULTR) aims to train unbiased ranking models from biased click logs, by explicitly modeling a generation process for user behavior and fitting click data based on examination hypothesis. Previous research found […]


Continue.. Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank