All Outputs (41)

ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation (2024)
Journal Article
Li, Z., Zheng, Y., Shan, D., Yang, S., Li, Q., Wang, B., …Shen, D. (2024). ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation. IEEE Transactions on Medical Imaging, 43(6), 2254-2265. https://doi.org/10.1109/TMI.2024.3363190

Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional la... Read More about ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation.

Using outlier elimination to assess learning-based correspondence matching methods (2024)
Journal Article
Ding, X., Luo, Y., Jie, B., Li, Q., & Cheng, Y. (2024). Using outlier elimination to assess learning-based correspondence matching methods. Information Sciences, 659, Article 120056. https://doi.org/10.1016/j.ins.2023.120056

Recently, deep learning (DL) technology has been widely used in correspondence matching. The learning-based models are usually trained on benign image pairs with partial overlaps. Since DL model is usually data-dependent, non-overlapping images may b... Read More about Using outlier elimination to assess learning-based correspondence matching methods.

NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction (2024)
Journal Article
Hong, Q., Yang, C., Chen, J., Li, Z., Wu, Q., Li, Q., & Tian, J. (2024). NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2024.3447088

3D reconstruction from multi-view images is considered as a longstanding problem in computer vision and graphics. In order to achieve high-fidelity geometry and appearance of 3D scenes, this paper proposes a novel geometric object learning method for... Read More about NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction.

LViT: Language meets Vision Transformer in Medical Image Segmentation (2023)
Journal Article
Li, Z., Li, Y., Li, Q., Wang, P., Guo, D., Lu, L., …Hong, Q. (2024). LViT: Language meets Vision Transformer in Medical Image Segmentation. IEEE Transactions on Medical Imaging, 43(1), 96-107. https://doi.org/10.1109/TMI.2023.3291719

Deep learning has been widely used in medical image segmentation and other aspects. However, the performance of existing medical image segmentation models has been limited by the challenge of obtaining sufficient high-quality labeled data due to the... Read More about LViT: Language meets Vision Transformer in Medical Image Segmentation.

A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification (2023)
Journal Article
Hong, Q., Lin, L., Li, Z., Li, Q., Yao, J., Wu, Q., …Tian, J. (in press). A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2023.3280646

Detecting pneumonia, especially coronavirus disease 2019 (COVID-19), from chest X-ray (CXR) images is one of the most effective ways for disease diagnosis and patient triage. The application of deep neural networks (DNNs) for CXR image classification... Read More about A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification.

Consensus Adversarial Defense Method Based on Augmented Examples (2022)
Journal Article
Ding, X., Cheng, Y., Luo, Y., Li, Q., & Gope, P. (2022). Consensus Adversarial Defense Method Based on Augmented Examples. IEEE Transactions on Industrial Informatics, https://doi.org/10.1109/TII.2022.3169973

Deep learning has been used in many computer-vision-based industrial Internet of Things applications. However, deep neural networks are vulnerable to adversarial examples that have been crafted specifically to fool a system while being imperceptible... Read More about Consensus Adversarial Defense Method Based on Augmented Examples.

High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations (2020)
Journal Article
Hong, Q., Li, Q., Wang, B., Tian, J., Xu, F., Liu, K., & Cheng, X. (2020). High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations. Computer Methods and Programs in Biomedicine, 196, Article 105598. https://doi.org/10.1016/j.cmpb.2020.105598

High-quality vascular modeling is crucial for blood flow simulations, i.e., computational fluid dynamics (CFD). As without an accurate geometric representation of the smooth vascular surface, it is impossible to make meaningful blood flow simulations... Read More about High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations.

Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality (2020)
Journal Article
Bian, W., Xu, D., Cheng, Y., Li, Q., Luo, Y., & Yu, Q. (2020). Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality. IET Biometrics, 9(5), 194-204. https://doi.org/10.1049/iet-bmt.2019.0121

In order to improve the quality of fingerprint with large noise, this paper proposes a fingerprint enhancement method by using a sparse representation of learned multi-scale classification dictionaries with reduced dimensionality. Mul... Read More about Fingerprint enhancement using multi-scale classification dictionaries with reduced dimensionality.

Local keypoint-based Faster R-CNN (2020)
Journal Article
Ding, X., Li, Q., Cheng, Y., Wang, J., Bian, W., & Jie, B. (in press). Local keypoint-based Faster R-CNN. Applied Intelligence, https://doi.org/10.1007/s10489-020-01665-9

Region-based Convolutional Neural Network (R-CNN) detectors have achieved state-of-the-art results on various challenging benchmarks. Although R-CNN has achieved high detection performance, the research of local information in producing candidates is... Read More about Local keypoint-based Faster R-CNN.

Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme (2020)
Journal Article
Bian, W., Gope, P., Cheng, Y., & Li, Q. (2020). Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme. Future generations computer systems : FGCS, 109, 45-55. https://doi.org/10.1016/j.future.2020.03.034

The fingerprint has long been used as one of the most important biological features in the field of biometrics. It is person-specific and remain identical though out one’s lifetime. Physically uncloneable functions (PUFs) have been used in authentica... Read More about Bio-AKA: An efficient fingerprint based two factor user authentication and key agreement scheme.

Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes (2020)
Journal Article
Yang, X., Han, X., Li, Q., He, L., Pang, M., & Jia, C. (2020). Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes. IEEE Access, 8, 40861-40880. https://doi.org/10.1109/ACCESS.2020.2976847

With the rapid development of point cloud processing technologies and the availability of a wide range of 3D capturing devices, a geometric object from the real world can be directly represented digitally as a dense and fine point cloud. Decomposing... Read More about Developing a Semantic-Driven Hybrid Segmentation Method for Point Clouds of 3D Shapes.

Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions (2019)
Journal Article
Qi, Q., Li, Q. D., Cheng, Y., & Hong, Q. Q. (2020). Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions. International Journal of Automation and Computing, 17(1), 30-43. https://doi.org/10.1007/s11633-019-1189-4

Fast high-precision patient-specific vascular tissue and geometric structure reconstruction is an essential task for vascular tissue engineering and computer-aided minimally invasive vascular disease diagnosis and surgery. In this paper, we present a... Read More about Skeleton Marching-based Parallel Vascular Geometry Reconstruction Using Implicit Functions.

High precision implicit modeling for patient-specific coronary arteries (2019)
Journal Article
Hong, Q., Li, Q., Wang, B., Liu, K., & Qi, Q. (2019). High precision implicit modeling for patient-specific coronary arteries. IEEE Access, 7, 72020-72029. https://doi.org/10.1109/ACCESS.2019.2920113

High precision geometric reconstruction of patient-specific coronary arteries plays a crucial role in visual diagnosis, treatment decision-making, and the evaluation of the therapeutic effect of interventions in coronary artery diseases. It is also a... Read More about High precision implicit modeling for patient-specific coronary arteries.

A Survey of the methods on fingerprint orientation field estimation (2019)
Journal Article
Bian, W., Xu, D., Li, Q., Cheng, Y., Jie, B., & Ding, X. (2019). A Survey of the methods on fingerprint orientation field estimation. IEEE Access, 7, 32644-32663. https://doi.org/10.1109/ACCESS.2019.2903601

Fingerprint orientation field (FOF) estimation plays a key role in enhancing the performance of the automated fingerprint identification system (AFIS): Accurate estimation of FOF can evidently improve the performance of AFIS. However, despite the eno... Read More about A Survey of the methods on fingerprint orientation field estimation.

High-performance geometric vascular modelling (2018)
Thesis
Qi, Q. (2018). High-performance geometric vascular modelling. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4221353

Image-based high-performance geometric vascular modelling and reconstruction is an essential component of computer-assisted surgery on the diagnosis, analysis and treatment of cardiovascular diseases. However, it is an extremely challenging task to e... Read More about High-performance geometric vascular modelling.

Towards additive manufacturing oriented geometric modeling using implicit functions (2018)
Journal Article
Li, Q., Hong, Q., Qi, Q., Ma, X., Han, X., & Tian, J. (2018). Towards additive manufacturing oriented geometric modeling using implicit functions. Visual Computing for Industry, Biomedicine, and Art, 1(1), Article 9. https://doi.org/10.1186/s42492-018-0009-y

Surface-based geometric modeling has many advantages in terms of visualization and traditional subtractive manufacturing using computer-numerical-control cutting-machine tools. However, it is not an ideal solution for additive manufacturing because t... Read More about Towards additive manufacturing oriented geometric modeling using implicit functions.

Thin Implicit Utah Teapot: Design for Additive Manufacturing (2018)
Presentation / Conference Contribution
Qi, Q., & Li, Q. (2018, July). Thin Implicit Utah Teapot: Design for Additive Manufacturing. Presented at The 18th IEEE International Conference on Computer and Information Technology

© 2018 IEEE. Converting a surface-based geometric object into a thin solid is an essential requirement for additive manufacturing. Although offset surface and thickening techniques have been widely used for this task, it is in general difficult to mo... Read More about Thin Implicit Utah Teapot: Design for Additive Manufacturing.

Prior knowledge-based deep learning method for indoor object recognition and application (2018)
Journal Article
Ding, X., Luo, Y., Li, Q., Cheng, Y., Cai, G., Munnoch, R., Xue, D., Yu, Q., Zheng, X., & Wang, B. (2018). Prior knowledge-based deep learning method for indoor object recognition and application. Systems Science and Control Engineering, 6(1), 249-257. https://doi.org/10.1080/21642583.2018.1482477

Indoor object recognition is a key task for indoor navigation by mobile robots. Although previous work has produced impressive results in recognizing known and familiar objects, the research of indoor object recognition for robot is still insufficien... Read More about Prior knowledge-based deep learning method for indoor object recognition and application.

Accurate geometry modeling of vasculatures using implicit fitting with 2D radial basis functions (2018)
Journal Article
Hong, Q., Li, Q., Wang, B., Liu, K., Lin, F., Lin, J., Cheng, X., Zhang, Z., & Zeng, M. (2018). Accurate geometry modeling of vasculatures using implicit fitting with 2D radial basis functions. Computer aided geometric design, 62, 206-216. https://doi.org/10.1016/j.cagd.2018.03.006

Accurate vascular geometry modeling is an essential task in computer assisted vascular surgery and therapy. This paper presents a vessel cross-section based implicit vascular modeling technique, which represents a vascular surface as a set of locally... Read More about Accurate geometry modeling of vasculatures using implicit fitting with 2D radial basis functions.

Multilevel refinable triangular PSP-splines (Tri-PSPS) (2015)
Journal Article
Li, Q., & Tian, J. (2015). Multilevel refinable triangular PSP-splines (Tri-PSPS). Computers & mathematics with applications, 70(8), 1781-1798. https://doi.org/10.1016/j.camwa.2015.07.017

A multi-level spline technique known as partial shape preserving splines (PSPS) (Li and Tian, 2011) has recently been developed for the design of piecewise polynomial freeform geometric surfaces, where the basis functions of the PSPS can be directly... Read More about Multilevel refinable triangular PSP-splines (Tri-PSPS).