Professor Jinchang Ren's Outputs (166)

FusDreamer: label-efficient remote sensing world model for multimodal data classification. (2025)
Journal Article
WANG, J., SONG, W., CHEN, H., REN, J. and ZHAO, H. [2025]. FusDreamer: label-efficient remote sensing world model for multimodal data classification. IEEE transactions on geoscience and remote sensing [online], Early Access. Available from: https://doi.org/10.1109/TGRS.2025.3554862

World models significantly enhance hierarchical understanding, improving data integration and learning efficiency. To explore the potential of the world model in the remote sensing (RS) field, this paper proposes a label-efficient remote sensing worl... Read More about FusDreamer: label-efficient remote sensing world model for multimodal data classification..

Entropy guidance hierarchical rich-scale feature network for remote sensing image semantic segmentation of high resolution. (2025)
Journal Article
ZHANG, H., LI, L., XIE, X., HE, Y., REN, J. and XIE, G. 2025. Entropy guidance hierarchical rich-scale feature network for remote sensing image semantic segmentation of high resolution. Applied intelligence [online], 55(6), article number 528. Available from: https://doi.org/10.1007/s10489-025-06433-1

Semantic segmentation of high-resolution remote sensing images (HRRSIs) is crucial for a wide range of applications, such as urban planning and disaster management. However, in HRRSIs, existing multiscale feature extraction and fusion methods often f... Read More about Entropy guidance hierarchical rich-scale feature network for remote sensing image semantic segmentation of high resolution..

MDDNet: multilevel difference-enhanced denoise network for unsupervised change detection in SAR images. (2025)
Presentation / Conference Contribution
ZONG, H., ZHANG, E., LI, X., ZHANG, H. and REN, J. 2025. MDDNet: multilevel difference-enhanced denoise network for unsupervised change detection in SAR images. In Proceedings of the 50th IEEE (Institute of Electrical and Electronics Engineers) International conference on acoustics, speech and signal processing 2025 (ICASSP 2025), 6-11 April 2025, Hyderabad, India. Piscataway: IEEE [online], article number 576. Available from: https://doi.org/10.1109/icassp49660.2025.10887943

Change detection in synthetic aperture radar (SAR) images is a hot yet highly challenging task in remote sensing. Existing unsupervised SAR change detection methods often struggle with inherent speckle noise and insufficiently utilize pseudo-labels,... Read More about MDDNet: multilevel difference-enhanced denoise network for unsupervised change detection in SAR images..

Binary quantization vision transformer for effective segmentation of red tide in multi-spectral remote sensing imagery. (2025)
Journal Article
XIE, Y., HOU, X., REN, J., ZHANG, X., MA, C. and ZHENG, J. 2025. Binary quantization vision transformer for effective segmentation of red tide in multi-spectral remote sensing imagery. IEEE Transactions on geoscience and remote sensing [online], 63, article number 4202814. Available from: https://doi.org/10.1109/TGRS.2025.3540784

As a global marine disaster, red tides pose serious threats to marine ecology and the blue economy, making their monitoring crucial for preventing harmful algal blooms and protecting the marine environment. In this study, satellite remote sensing was... Read More about Binary quantization vision transformer for effective segmentation of red tide in multi-spectral remote sensing imagery..

An optimized lightweight real-time detection network model for IoT embedded devices. (2025)
Journal Article
CHEN, R., WANG, P., LIN, B., WANG, L., ZENG, X., HU, X., YUAN, J., LI, J., REN, J. and ZHAO, H. 2025. An optimized lightweight real-time detection network model for IoT embedded devices. Scientific reports [online], 15(1), article number 3839. Available from: https://doi.org/10.1038/s41598-025-88439-w

With the rapid development of Internet of Things (IoT) technology, embedded devices in various computer vision scenarios can realize real-time target detection and recognition tasks, such as intelligent manufacturing, automatic driving, smart home, a... Read More about An optimized lightweight real-time detection network model for IoT embedded devices..

Frequency-domain guided swin transformer and global-local feature integration for remote sensing images semantic segmentation. (2025)
Journal Article
ZHANG, H., XIE, G., LI, L., XIE, X. and REN, J. 2025. Frequency-domain guided swin transformer and global-local feature integration for remote sensing images semantic segmentation. IEEE Transactions on geoscience and remote sensing [online], 63, article number 5612611. Available from: https://doi.org/10.1109/TGRS.2025.3535724

Convolutional Neural Networks (CNNs), transformers, and the hybrid methods have been significant application in remote sensing. However, existing methods are limited in effectively modeling frequency domain information, which affects their ability to... Read More about Frequency-domain guided swin transformer and global-local feature integration for remote sensing images semantic segmentation..

ChangeDA: depth-augmented multi-task network for remote sensing change detection via differential analysis. (2025)
Journal Article
MENG, J., XU, X., ZHANG, Z., LI, P., XIE, G., REN, J. and ZHENG, Y. 2025. ChangeDA: depth-augmented multi-task network for remote sensing change detection via differential analysis. IEEE Transactions on geoscience and remote sensing [online], 63, article number 5616119. Available from: https://doi.org/10.1109/TGRS.2025.3532468

In the field of Remote Sensing Change Detection (RSCD), accurately identifying significant changes between bitemporal images is essential for environmental monitoring, urban planning, and disaster assessment. In recent years, advancements in deep lea... Read More about ChangeDA: depth-augmented multi-task network for remote sensing change detection via differential analysis..

GASSM: global attention and state space model based end-to-end hyperspectral change detection. (2025)
Journal Article
LI, Y., REN, J., FU, H. and SUN, G. 2025. GASSM: global attention and state space model based end-to-end hyperspectral change detection. Journal of the Franklin Institute [online], 362(3), article number 107424. Available from: https://doi.org/10.1016/j.jfranklin.2024.107424

As an essential task to identify anomalies and monitor changes over time, change detection enables detailed earth observation in remote sensing. By combining both the rich spectral information and spatial image, hyperspectral images (HSI) have offere... Read More about GASSM: global attention and state space model based end-to-end hyperspectral change detection..

Protecting visual data privacy in offshore industry via underwater image inpainting. (2024)
Presentation / Conference Contribution
TOLIE, H.F., REN, J., CHEN, R. and ZHAO, H. 2024. Protecting visual data privacy in offshore industry via underwater image inpainting. In Proceedings of the 9th International conference on image, vision and computing 2024 (ICIVC 2024), 15-17 July 2024, Suzhou, China. Piscataway: IEEE [online], pages 281-286. Available from: https://doi.org/10.1109/ICIVC61627.2024.10837433

Leveraging advanced artificial intelligence (AI) methodologies offers the advantage of incorporating multiple expert viewpoints, thereby facilitating a more comprehensive inspection of underwater infrastructure. However, the implementation of AI tech... Read More about Protecting visual data privacy in offshore industry via underwater image inpainting..

Special issue on the application of remote sensing spatio-temporal big data to effective environmental monitoring and sustainable development. (2024)
Journal Article
SUN, G., REN, J., SUN, Q. and JIA, M. 2024. Special issue on the application of remote sensing spatio-temporal big data to effective environmental monitoring and sustainable development. Journal of geodesy and geoinformation science [online], 7(4), pages 2-3. Available from: https://doi.org/10.11947/j.JGGS.2024.0401

The rapid advancement of remote sensing, data science, and geographic information technology has ushered in an era of substantial information explosion. Massive spatio-temporal big data provides rich data resources and technical means have facilitate... Read More about Special issue on the application of remote sensing spatio-temporal big data to effective environmental monitoring and sustainable development..

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..

Horizons in imaging. (2024)
Journal Article
PIVA, A., ZHANG, L. and REN, J. 2024. Horizons in imaging. Frontiers in imaging [online], 3, article number 1530335. Available from: https://doi.org/10.3389/fimag.2024.1530335

Over the past several years, imaging technology has undergone a rapid wave of innovation, with new applications reshaping a wide range of fields, from healthcare and environmental monitoring to entertainment and civil security. This rapid progression... Read More about Horizons in imaging..

ICSF: integrating inter-modal and cross-modal learning framework for self-supervised heterogeneous change detection. (2024)
Journal Article
ZHANG, E., ZONG, H., LI, X., FENG, M. and REN, J. 2025. ICSF: integrating inter-modal and cross-modal learning framework for self-supervised heterogeneous change detection. IEEE transactions on geoscience and remote sensing [online], 63, 501516. Available from: https://doi.org/10.1109/TGRS.2024.3519195

Heterogeneous change detection (HCD) is a process to determine the change information by analyzing heterogeneous images of the same geographic location taken at different times, which plays an important role in remote sensing applications such as dis... Read More about ICSF: integrating inter-modal and cross-modal learning framework for self-supervised heterogeneous change detection..

Dual teacher: improving the reliability of pseudo labels for semi-supervised oriented object detection. (2024)
Journal Article
FANG, Z., REN, J., ZHENG, J., CHEN, R. and ZHAO, H. 2025. Dual teacher: improving the reliability of pseudo labels for semi-supervised oriented object detection. IEEE transactions on geoscience and remote sensing [online], 63, 5602515. Available from: https://doi.org/10.1109/TGRS.2024.3519173

Oriented object detection in remote sensing is a critical task for accurately location and measurement of the interested targets. Despite of its success in object detection, deep learning-based detectors rely heavily on extensive data annotation. How... Read More about Dual teacher: improving the reliability of pseudo labels for semi-supervised oriented object detection..

Blind sonar image quality assessment via machine learning: leveraging micro- and macro-scale texture and contour features in the wavelet domain. (2024)
Journal Article
TOLIE, H.F., REN, J., CHEN, R., ZHAO, H. and ELYAN, E. 2025. Blind sonar image quality assessment via machine learning: leveraging micro- and macro-scale texture and contour features in the wavelet domain. Engineering applications of artificial intelligence [online], 141, article number 109730. Available from: https://doi.org/10.1016/j.engappai.2024.109730

In subsea environments, sound navigation and ranging (SONAR) images are widely used for exploring and monitoring infrastructures due to their robustness and insensitivity to low-light conditions. However, their quality can degrade during acquisition... Read More about Blind sonar image quality assessment via machine learning: leveraging micro- and macro-scale texture and contour features in the wavelet domain..

High-resolution remote sensing image change detection based on Fourier feature interaction and multi-scale perception. (2024)
Journal Article
CHEN, Y., FENG, S., ZHAO, C., SU, N., LI, W., TAO, R. and REN, J. 2024. High-resolution remote sensing image change detection based on Fourier feature interaction and multi-scale perception. IEEE transactions on geoscience and remote sensing [online], 62, article number 3500073. Available from: https://doi.org/10.1109/TGRS.2024.3500073

As a significant means of Earth observation, change detection in high-resolution remote sensing images has received extensive attention. Nevertheless, the variability in imaging conditions introduces style discrepancies and a range of pseudo change r... Read More about High-resolution remote sensing image change detection based on Fourier feature interaction and multi-scale perception..

Enhancing underwater situational awareness: RealSense camera integration with deep learning for improved depth perception and distance measurement. (2024)
Presentation / Conference Contribution
TOLIE, H.F., REN, J., HASAN, M.J. and KANNAN, S. 2024. Enhancing underwater situational awareness: RealSense camera integration with deep learning for improved depth perception and distance measurement. In Bouma, H., Prabhu, R., Yitzhaky, Y. and Kuijf, H.J. (eds.) Artificial intelligence for security and defence applications II: proceedings of the 2024 SPIE Security + defence, 16-20 September 2024, Edinburgh, UK. Proceedings of SPIE, 13206. Bellingham, WA; SPIE [online], paper 1320605. Available from: https://doi.org/10.1117/12.3030972

This work presents a depth image refinement technique designed to enhance the usability of a commercial camera in underwater environments. Stereo vision-based depth cameras offer dense data that is well-suited for accurate environmental understanding... Read More about Enhancing underwater situational awareness: RealSense camera integration with deep learning for improved depth perception and distance measurement..

Detection of black tea fermentation quality based on optimized deep neural network and hyperspectral imaging. (2024)
Journal Article
HUANG, M., TANG, Y., TAN, Z., REN, J., HE, Y. and HUANG, H. 2024. Detection of black tea fermentation quality based on optimized deep neural network and hyperspectral imaging. Infrared physics and technology [online], 143, article number 105625. Available from: https://doi.org/10.1016/j.infrared.2024.105625

The quality of black tea significantly relies on its fermentation process. Nevertheless, achieving precise and objective evaluations remains challenging due to the subjective nature of manual judgment involved in quality monitoring. To address this p... Read More about Detection of black tea fermentation quality based on optimized deep neural network and hyperspectral imaging..

MDAR: a multiscale features-based network for remotely measuring human heart rate utilizing dual-branch architecture and alternating frame shifts in facial videos. (2024)
Journal Article
ZHANG, L., REN, J., ZHAO, S. and WU, P. 2024. MDAR: a multiscale features-based network for remotely measuring human heart rate utilizing dual-branch architecture and alternating frame shifts in facial videos. Sensors [online], 24(21), article number 6791. Available from: https://doi.org/10.3390/s24216791

Remote photoplethysmography (rPPG) refers to a non-contact technique that measures heart rate through analyzing the subtle signal changes of facial blood flow captured by video sensors. It is widely used in contactless medical monitoring, remote heal... Read More about MDAR: a multiscale features-based network for remotely measuring human heart rate utilizing dual-branch architecture and alternating frame shifts in facial videos..

Promptable sonar image segmentation for distance measurement using SAM. (2024)
Presentation / Conference Contribution
TOLIE, H.F., REN, J., HASAN, M.J., KANNAN, S. and FOUGH, N. 2024. Promptable sonar image segmentation for distance measurement using SAM. In Proceedings of the 2024 IEEE (Institute of Electrical and Electronics Engineers) International workshop on Metrology for the sea; learning to measure sea health parameters (IEEE MetroSea 2024), 14-16 October 2024, Portorose, Slovenia. Piscataway: IEEE [online], pages 229-233. Available from: https://doi.org/10.1109/metrosea62823.2024.10765703

The subsea environment presents numerous challenges for robotic vision, including non-uniform light attenuation, backscattering, floating particles, and low-light conditions, which significantly degrade underwater images. This degradation impacts rob... Read More about Promptable sonar image segmentation for distance measurement using SAM..