Search Results for author: Yiting Wang

Found 6 papers, 0 papers with code

Benchmarking the Robustness of Panoptic Segmentation for Automated Driving

no code implementations23 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.

Benchmarking Decision Making +3

ClassLIE: Structure- and Illumination-Adaptive Classification for Low-Light Image Enhancement

no code implementations20 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.

Low-Light Image Enhancement SSIM

Establishing group-level brain structural connectivity incorporating anatomical knowledge under latent space modeling

no code implementations21 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.

Ensemble Ranking Model with Multiple Pretraining Strategies for Web Search

no code implementations18 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.

Learning-To-Rank

Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank

no code implementations15 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.

Learning-To-Rank

GenAD: General Representations of Multivariate Time Series for Anomaly Detection

no code implementations1 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.

Management Time Series +2

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