All Outputs (53)

Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach (2024)
Thesis
Dulian, . A. Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4625808

Complex environments manifest a high level of complexity and it is of critical importance that the safety systems embedded within autonomous vehicles (AVs) are able to accurately anticipate short-term future motion of agents in close proximity. This... Read More about Short-term motion prediction of autonomous vehicles in complex environments: A Deep Learning approach.

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.

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images (2022)
Journal Article
Quintero, P., Benoit, D., Cheng, Y., Moore, C., & Beavis, A. (2022). Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images. Physics in Medicine and Biology, 67(24), Article 245001. https://doi.org/10.1088/1361-6560/aca38a

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose d... Read More about Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.

The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation (2022)
Data
Chang, Y., Cheng, Y., Murray, J., Huang, S., & Shi, G. (2022). The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation. [Dataset]

The dataset contains image samples and Multi-task labels (i.e., regression and classification labels) collected from onboard UAV sensors in real-world indoor environments. By transforming the original labels following the instructions at: https://git... Read More about The HDIN dataset: A Real-world Indoor UAV Dataset with Multi-task Labels for Visual-based Navigation.

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.

An AI-Driven Secure and Intelligent Robotic Delivery System (2022)
Journal Article
Wang, W., Gope, P., & Cheng, Y. (in press). An AI-Driven Secure and Intelligent Robotic Delivery System. IEEE Transactions on Engineering Management, https://doi.org/10.1109/TEM.2022.3142282

Last-mile delivery has gained much popularity in recent years, it accounts for about half of the whole logistics cost. Unlike container transportation, companies must hire significant number of employees to deliver packages to the customers. Therefor... Read More about An AI-Driven Secure and Intelligent Robotic Delivery System.

A Novel Robust Low-rank Multi-view Diversity Optimization Model with Adaptive-Weighting Based Manifold Learning (2021)
Journal Article
Tan, J., Yang, Z., Ren, J., Wang, B., Cheng, Y., & Ling, W. K. (2022). A Novel Robust Low-rank Multi-view Diversity Optimization Model with Adaptive-Weighting Based Manifold Learning. Pattern Recognition, 122, Article 108298. https://doi.org/10.1016/j.patcog.2021.108298

Multi-view clustering has become a hot yet challenging topic, due mainly to the independence of and information complementarity between different views. Although good results are achieved to a certain extent from typical methods including multi-view... Read More about A Novel Robust Low-rank Multi-view Diversity Optimization Model with Adaptive-Weighting Based Manifold Learning.

Msb r‐cnn: A multi‐stage balanced defect detection network (2021)
Journal Article
Xu, Z., Lan, S., Yang, Z., Cao, J., Wu, Z., & Cheng, Y. (2021). Msb r‐cnn: A multi‐stage balanced defect detection network. Electronics, 10(16), Article 1924. https://doi.org/10.3390/electronics10161924

Deep learning networks are applied for defect detection, among which Cascade R‐CNN is a multi‐stage object detection network and is state of the art in terms of accuracy and efficiency. However, it is still a challenge for Cascade R‐CNN to deal with... Read More about Msb r‐cnn: A multi‐stage balanced defect detection network.

Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator (2021)
Journal Article
Quintero, P., Cheng, Y., Benoit, D., Moore, C., & Beavis, A. (2021). Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator. British Journal of Radiology, 94(1122), Article 20201011. https://doi.org/10.1259/bjr.20201011

OBJECTIVE: High levels of beam modulation complexity (MC) and monitor units (MU) can compromise the plan deliverability of intensity-modulated radiotherapy treatments. Our study evaluates the effect of three treatment planning system (TPS) parameters... Read More about Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator.

SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning (2021)
Journal Article
Tan, J., Yang, Z., Cheng, Y., Ye, J., Wang, B., & Dai, Q. (2021). SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning. Pattern Recognition, 117, Article 107987. https://doi.org/10.1016/j.patcog.2021.107987

Sparse representation and cooperative learning are two representative technologies in the field of multi-view spectral clustering. The former can effectively extract features of multiple views by the removal of redundant information contained in each... Read More about SRAGL-AWCL: A two-step multi-view clustering via sparse representation and adaptive weighted cooperative learning.

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.

Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images (2020)
Journal Article
Yang, Z., Cao, F., Cheng, Y., Ling, W.-K., & Hu, R. (in press). Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images. IEEE transactions on geoscience and remote sensing : a publication of the IEEE Geoscience and Remote Sensing Society, 1-16. https://doi.org/10.1109/tgrs.2020.2988900

Despite the successful applications of probabilistic collaborative representation classification (PCRC) in pattern classification, it still suffers from two challenges when being applied on hyperspectral images (HSIs) classification: 1) ineffective f... Read More about Locality Regularized Robust-PCRC: A Novel Simultaneous Feature Extraction and Classification Framework for Hyperspectral Images.

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.

Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography (2019)
Journal Article
Huang, C., Lan, Y., Chen, S., Liu, Q., Luo, X., Xu, G., Zhou, W., Lin, F., Peng, Y., Ng, E. Y. K., Cheng, Y., Zeng, N., Zhang, G., & Che, W. (2019). Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography. Complexity, 2019, 1-10. https://doi.org/10.1155/2019/5712594

Despite the new ideas were inspired in medical treatment by the rapid advancement of three-dimensional (3D) printing technology, there is still rare research work reported on 3D printing of coronary arteries being documented in the literature. In thi... Read More about Patient-Specific Coronary Artery 3D Printing Based on Intravascular Optical Coherence Tomography and Coronary Angiography.

An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health (2019)
Journal Article
Xu, G., Lan, Y., Zhou, W., Huang, C., Li, W., Zhang, W., Zhang, G., Ng, E. Y. K., Cheng, Y., Peng, Y., & Che, W. (2019). An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health. IEEE Access, 7, 173866-173874. https://doi.org/10.1109/ACCESS.2019.2957149

Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, suc... Read More about An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health.

An enhanced secure delegation-based anonymous authentication protocol for PCSs (2019)
Journal Article
Gope, P., Ghayvat, H., Cheng, Y., & Kabir, S. (2019). An enhanced secure delegation-based anonymous authentication protocol for PCSs. International Journal of Communication Systems, Article e4199. https://doi.org/10.1002/dac.4199

Rapid development of wireless networks brings about many security problems in portable communication systems (PCSs), which can provide mobile users with an opportunity to enjoy global roaming services. In this regard, designing a secure user authenti... Read More about An enhanced secure delegation-based anonymous authentication protocol for PCSs.

Lumen contour segmentation in ivoct based on n-type cnn (2019)
Journal Article
Tang, J., Lan, Y., Chen, S., Zhong, Y., Huang, C., Peng, Y., Liu, Q., Cheng, Y., Chen, F., & Che, W. (2019). Lumen contour segmentation in ivoct based on n-type cnn. IEEE Access, 7, 135573-135581. https://doi.org/10.1109/ACCESS.2019.2941899

Automatic segmentation of lumen contour plays an important role in medical imaging and diagnosis, which is the first step towards the evaluation of morphology of vessels under analysis and the identification of possible atherosclerotic lesions. Meanw... Read More about Lumen contour segmentation in ivoct based on n-type cnn.

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.

Ensemble multiboost based on ripper classifier for prediction of imbalanced software defect data (2019)
Journal Article
He, H., Zhang, X., Wang, Q., Ren, J., Liu, J., Zhao, X., & Cheng, Y. (2019). Ensemble multiboost based on ripper classifier for prediction of imbalanced software defect data. IEEE Access, 7, 110333-110343. https://doi.org/10.1109/ACCESS.2019.2934128

Identifying defective software entities is essential to ensure software quality during software development. However, the high dimensionality and class distribution imbalance of software defect data seriously affect software defect prediction perform... Read More about Ensemble multiboost based on ripper classifier for prediction of imbalanced software defect data.