All Outputs (7)

Effective marine monitoring with multimodal sensing and improved underwater robotic perception towards environmental protection and smart energy transition. (2024)
Journal Article
FARHADI TOLIE, H., REN, J., HASAN, M.J., MA, P, KENNAN, S. and LI, Y. 2024. Effective marine monitoring with multimodal sensing and improved underwater robotic perception towards environmental protection and smart energy transition. Journal of geodesy and geoinformation science [online], 7(4), pages 19-35. Available from: https://doi.org/10.11947/j.JGGS.2024.0403

Effective underwater sensing is crucial for environmental protection and sustainable energy transitions, particularly as we face growing challenges in marine ecosystem monitoring, resource management, and the need for efficient energy infrastructure.... Read More about Effective marine monitoring with multimodal sensing and improved underwater robotic perception towards environmental protection and smart energy transition..

Hyperspectral imagery quality assessment and band reconstruction using the Prophet model. (2024)
Journal Article
MA, P., REN, J., GAO, Z., LI, Y. and CHEN, R. [2024]. Hyperspectral imagery quality assessment and band reconstruction using the Prophet model. CAAI transactions on intelligence technology [online], Early View. Available from: https://doi.org/10.1049/cit2.12373

In Hyperspectral Imaging (HSI), the detrimental influence of noise and distortions on data quality is profound, which has severely affected the following-on analytics and decision-making such as land mapping. This study presents an innovative framewo... Read More about Hyperspectral imagery quality assessment and band reconstruction using the Prophet model..

Sparse autoencoder based hyperspectral anomaly detection with the singular spectrum analysis based spectral denoising. (2024)
Presentation / Conference Contribution
LI, Y., REN, J., GAO, Z. and SUN, G. 2024. Sparse autoencoder based hyperspectral anomaly detection with the singular spectrum analysis based spectral denoising. In Proceedings of the 2024 IEEE International geoscience and remote sensing symposium (IGARSS 2024), Athens, Greece, 7-12 July 2024. Piscataway: IEEE [online], pages 9210-9213. Available from: https://doi.org/10.1109/igarss53475.2024.10641314

As an effective tool for monitoring surface irregularities in remote sensing, hyperspectral anomaly detection (HAD) has garnered increasing attention. However, how to improve the detection accuracy remains a formidable challenge, due mainly to the no... Read More about Sparse autoencoder based hyperspectral anomaly detection with the singular spectrum analysis based spectral denoising..

SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection. (2024)
Journal Article
LI, Y., REN, J., YAN, Y., SUN, G. and MA, P. 2024. SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection. Remote sensing [online], 16(3), article number 2353. Available from: https://doi.org/10.3390/rs16132353

As an emerging research hotspot in contemporary remote sensing, hyperspectral change detection (HCD) has attracted increasing attention in remote sensing Earth observation, covering land mapping changes and anomaly detection. This is primarily attrib... Read More about SSA-LHCD: a singular spectrum analysis-driven lightweight network with 2-D self-attention for hyperspectral change detection..

ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection. (2024)
Journal Article
LI, Y., REN, J., YAN, Y., MA, P., ASSAAD, M. and GAO, Z. 2024. ABBD: accumulated band-wise binary distancing for unsupervised parameter-free hyperspectral change detection. IEEE journal of selected topics in applied earth observations and remote sensing [online], 17, pages 9880-9893. Available from: https://doi.org/10.1109/JSTARS.2024.3407212

As a fundamental task in remote sensing earth observation, hyperspectral change detection (HCD) aims to identify the changed pixels in bi-temporal hyperspectral images (HSIs). However, the water-absorption effect, poor weather conditions, noise and i... Read More about ABBD: accumulated band-wise binary distancing for unsupervised parameter-free 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..

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..