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Li Liu

5 papers indexed

openalexBuildings2026-07-23

Deep Learning-Based Aesthetic Perception of Spring Zone Street View Images: A Case Study of Jinan Mingfu City Area

Lin Chen, Li Liu, Zhe Liu

To address the existing gap in quantitative evaluation regarding the integrated visual effect of spring water landscapes and street spaces within Historical and Cultural Neighborhoods of Spring Zone, the Jinan Mingfu City area is selected as a typical case for this research. A qu…

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arxivcs.SDcs.AIcs.CR2026-07-18

Do Speech Tokens Leak Voiceprints? Speaker Inversion Attacks Against End-to-End Speech Language Models

Ye Lu, Yihan Yan, Zhaoyang Zhang, Zhitao Ou, Runze Liu, Li Liu, et al.

End-to-end speech language models increasingly represent user speech with speech tokens rather than relying exclusively on cascaded ASR--LLM--TTS pipelines. Although these tokens support expressive and low-latency spoken interaction, they may also preserve sensitive speaker chara…

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arxivcs.CVcs.RO2026-07-10

Toward Active Object Detection for UAVs in the Wild: A Large-Scale Dataset, Benchmark and Method

Tianpeng Liu, Xinhua Jiang, Li Liu, Qinmu Shen, Siwei Tang, Zhen Liu, et al.

Object detection is a fundamental component in numerous Unmanned Aerial Vehicle (UAV) applications, yet it has long been plagued by hindrances like occlusion or target pixel scarcity. Active Object Detection (AOD) provides a novel paradigm to address these challenges via active v…

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crossrefCancers2023-09-13Cited by 18

MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer

Xiaofeng Qiao, Xiling Gu, Yunfan Liu, Xin Shu, Guangyong Ai, Shuang Qian, et al.

Purpose: The Ki67 index and the Gleason grade group (GGG) are vital prognostic indicators of prostate cancer (PCa). This study investigated the value of biparametric magnetic resonance imaging (bpMRI) radiomics feature-based machine learning (ML) models in predicting the Ki67 ind…

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