Search Results for author: Zhang Li

Found 8 papers, 1 papers with code

Oriented Object Detection in Optical Remote Sensing Images using Deep Learning: A Survey

no code implementations21 Feb 2023 Kun Wang, Zi Wang, Zhang Li, Ang Su, Xichao Teng, Minhao Liu, Qifeng Yu

Oriented object detection is one of the most fundamental and challenging tasks in remote sensing, aiming at locating the oriented objects of numerous predefined object categories.

object-detection Object Detection +1

LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset

no code implementations16 Jan 2023 Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni, Zhang Li, Tao Tan, Abhir Bhalerao, Jiabo Ma, Jiamei Sun, Johnathan Pocock, Josien P. W. Pluim, Navid Alemi Koohbanani, Raja Muhammad Saad Bashir, Shan E Ahmed Raza, Sibo Liu, Simon Graham, Suzanne Wetstein, Syed Ali Khurram, Thomas Watson, Nasir Rajpoot, Mitko Veta, Francesco Ciompi

Additionally, we present post-competition results where we show how the presented methods perform on an independent set of lung cancer slides, which was not part of the initial competition, as well as a comparison on lymphocyte assessment between presented methods and a panel of pathologists.

Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints

no code implementations23 Dec 2022 Zi Wang, Minglin Chen, Yulan Guo, Zhang Li, Qifeng Yu

Recently, unsupervised domain adaptation in satellite pose estimation has gained increasing attention, aiming at alleviating the annotation cost for training deep models.

Pose Estimation Pseudo Label +1

Minimal Solutions for Relative Pose with a Single Affine Correspondence

no code implementations CVPR 2020 Banglei Guan, Ji Zhao, Zhang Li, Fang Sun, Friedrich Fraundorfer

In this paper we present four cases of minimal solutions for two-view relative pose estimation by exploiting the affine transformation between feature points and we demonstrate efficient solvers for these cases.

Motion Estimation Outlier Detection +1

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning

no code implementations10 Feb 2018 Tao Tan, Zhang Li, Haixia Liu, Ping Liu, Wenfang Tang, Hui Li, Yue Sun, Yusheng Yan, Keyu Li, Tao Xu, Shanshan Wan, Ke Lou, Jun Xu, Huiming Ying, Quchang Ouyang, Yuling Tang, Zheyu Hu, Qiang Li

To help doctors to be more selective on biopsies and provide a second opinion on diagnosis, in this work, we propose a computer-aided diagnosis (CAD) system for lung diseases including cancers and tuberculosis (TB).

Transfer Learning

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