All Outputs (10)

Advanced modelling and analytics for effective change and anomaly detection in hyperspectral images. (2024)
Thesis
LI, Y. 2024. Advanced modelling and analytics for effective change and anomaly detection in hyperspectral images. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://doi.org/10.48526/rgu-wt-2795662

The main objective of this research is to design and implement novel models and analytics techniques for hyperspectral change detection and anomaly detection. With the widespread applications of hyperspectral imagery (HSI) in fields such as remote se... Read More about Advanced modelling and analytics for effective change and anomaly detection in hyperspectral images..

Image enhancement for UAV visual SLAM applications: analysis and evaluation. (2024)
Presentation / Conference Contribution
TIAN, Y., YUE, H. and REN, J. 2024. Image enhancement for UAV visual SLAM applications: analysis and evaluation. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 51-61. Available from: https://doi.org/10.1007/978-981-97-1417-9_20.

Although simultaneous localisation and mapping (SLAM) has been widely applied in a wide range of robotics and navigation applications, its applicability is severely affected by the quality of the acquired images, especially for those in unmanned aeri... Read More about Image enhancement for UAV visual SLAM applications: analysis and evaluation..

MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection. (2024)
Presentation / Conference Contribution
LI, Y., YAN, Y. and REN, C., LIU, Q. and SUN, H. 2024. MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 51-61. Available from: https://doi.org/10.1007/978-981-97-1417-9_5.

Hyperspectral change detection plays a critical role in remote sensing by leveraging spectral and spatial information for accurate land cover variation identification. Long short-term memory (LSTM) has demonstrated its effectiveness in capturing depe... Read More about MLM-LSTM: multi-layer memory learning framework based on LSTM for hyperspectral change detection..

Underwater object detection for smooth and autonomous operations of naval missions: a pilot Dataset. (2024)
Presentation / Conference Contribution
YAN, Y., LI, Y., LIN, H., SARKER, M.M.K., REN, J. and MCCALL, J. 2024. Underwater object detection for smooth and autonomous operations of naval missions: a pilot dataset. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 113-122. Available from: https://doi.org/10.1007/978-981-97-1417-9_11

Underwater object detection is essential for ensuring autonomous naval operations. However, this task is challenging due to the complexities of underwater environments that often degrade image quality, thereby hampering the performance of detection a... Read More about Underwater object detection for smooth and autonomous operations of naval missions: a pilot Dataset..

HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion. (2024)
Presentation / Conference Contribution
WU, Y., ZHANG, X., LIU, Q., XUE, D., SUN, H. and REN, J. 2024. HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 251-263. Available from: https://doi.org/10.1007/978-981-97-1417-9_24

Multi-object tracking in satellite videos (SV-MOT) is one of the most challenging tasks in remote sensing, its difficulty mainly comes from the low spatial resolution, small target and extremely complex background. The widely studied multi-object tra... Read More about HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion..

Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies. (2024)
Presentation / Conference Contribution
HASAN, M.J., ELYAN, E., YAN, Y., REN, J. and SARKER, M.M.K. 2024. Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 220-228. Available from: https://doi.org/10.1007/978-981-97-1417-9_21

Retrofitting and thermographic survey (TS) companies in Scotland collaborate with social housing providers to tackle fuel poverty. They employ ground-level infrared (IR) camera-based-TSs (GIRTSs) for collecting thermal images to identify the heat los... Read More about Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies..

Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset] (2023)
Data
MA, P., REN, J., SUN, G., ZHAO, H., JIA, X., YAN, Y. and ZABALZA, J. 2023. Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset]. IEEE transactions on geoscience and remote sensing [online], 61, article 5508912. Available from: https://doi.org/10.1109/tgrs.2023.3260634/mm1

In this paper, we have proposed Multiscale Superpixelwise Prophet model (MSPM), a novel spectral-spatial feature mining framework for noise-robust feature extraction and effective data classification of the HSI. First, we demonstrate that the Prophet... Read More about Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset].

MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset] (2022)
Data
LI, M., WANG, Z., REN, J. and SUN, M. 2022. MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset]. Hosted on GitHub [online]. Available from: https://github.com/Lm0324/MVVA-Net

Most of the existing video aesthetic quality assessment datasets (as seen in Table 1) are not public, some are not large enough, which makes the trained depth model perform poorly and some are based on the professionalism of video shooting or the rat... Read More about MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset].

VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program. (2019)
Presentation / Conference Contribution
YAN, Y., ZHAO, S., FANG, Y., LIU, Y., CHEN, Z. and REN, J. 2020. VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program. In Ren, J., Hussain, A., Zhao, H., Huang, K., Zheng, J., Cai, J., Chen, R. and Xiao, Y. (eds.). 2020. Advances in brain inspired cognitive systems: proceedings of the 10th Brain inspired cognitive systems (BCIS) international conference 2019 (BCIS 2019), 13-14 July 2019, Guangzhou, China. Lecture notes in computer science, 11691. Cham: Springer [online], pages 283-292. Available from: https://doi.org/10.1007/978-3-030-39431-8_27

In this paper, we introduce a new concept in VIP-STB, a funded project through Agri-Tech in China: Newton Network+ (ATCNN), in developing feasible solutions towards scaling-up STB from village level to upper level via some generic models and systems.... Read More about VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program..

Deep Learning Based Single Image Super-Resolution: A Survey (2018)
Presentation / Conference Contribution
HA, V.K., REN, J., XU, X., ZHAO, S. XIE, G. and VARGAS, V.M. 2018. Deep learning based single image super-resolution: a survey. In Ren, J., Hussain, A., Zheng, J., Liu, C.-L., Luo, B., Zhao, H. and Zhao, X. (eds.) Advances in brain inspired cognitive systems: proceedings of 9th International conference brain inspired cognitive systems 2018 (BICS 2018), 7-8 July 2018, Xi'an, China. Lecture notes in computer sciences, 10989. Cham: Springer [online], pages 106-119. Available from: https://doi.org/10.1007/978-3-030-00563-4_11

Image super-resolution is a process of obtaining one or more high-resolution image from single or multiple samples of low-resolution images. Due to its wide applications, a number of different techniques have been developed recently, including interp... Read More about Deep Learning Based Single Image Super-Resolution: A Survey.