no code implementations • 14 Apr 2024 • Haonan Zhao, Yiting Wang, Thomas Bashford-Rogers, Valentina Donzella, Kurt Debattista
A comparative analysis of these methods is presented from the perspective of image quality and perception.
no code implementations • 23 Feb 2024 • Yiting Wang, Haonan Zhao, Daniel Gummadi, Mehrdad Dianati, Kurt Debattista, Valentina Donzella
Motivated by such a need, this work proposes a unifying pipeline to assess the robustness of panoptic segmentation models for AAD, correlating it with traditional image quality.
no code implementations • 20 Dec 2023 • Zixiang Wei, Yiting Wang, Lichao Sun, Athanasios V. Vasilakos, Lin Wang
A class prediction block is then designed to classify the degradation information by calculating the structure similarity scores on the reflectance map and mean square error on the illumination map.
no code implementations • 21 Feb 2023 • Selena Wang, Yiting Wang, Frederick H. Xu, Li Shen, Yize Zhao
By applying the ABC model to study brain structural connectivity stratified by sex among Alzheimer's Disease (AD) subjects and healthy controls incorporating the anatomical attributes (volume, thickness and area) on nodes, our method shows superior predictive power on out-of-sample structural connectivity and identifies meaningful sex-specific network neuromarkers for AD.
no code implementations • 18 Feb 2023 • Xiaojie Sun, Lulu Yu, Yiting Wang, Keping Bi, Jiafeng Guo
Then we fine-tune several pre-trained models and train an ensemble model to aggregate all the predictions from various pre-trained models with human-annotation data in the fine-tuning stage.
no code implementations • 15 Feb 2023 • Lulu Yu, Yiting Wang, Xiaojie Sun, Keping Bi, Jiafeng Guo
Unbiased learning to rank (ULTR) aims to mitigate various biases existing in user clicks, such as position bias, trust bias, presentation bias, and learn an effective ranker.
no code implementations • 1 Jan 2021 • Xiaolei Hua, Su Wang, Lin Zhu, Dong Zhou, Junlan Feng, Yiting Wang, Chao Deng, Shuo Wang, Mingtao Mei
However, due to complex correlations and various temporal patterns of large-scale multivariate time series, a general unsupervised anomaly detection model with higher F1-score and Timeliness remains a challenging task.