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- DTCNet: Transformer-CNN Distillation for Super-Resolution of Remote Sensing Image
- IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSINGLin, Cong Mao, Xin Qiu, Chenghao Zou, Lilan 出版年：2024
- Super-resolution reconstruction technology is a crucial approach to enhance the quality of remote sensing optical images. Currently, the mainstream reconstruction methods leverage convolutional neural networks (CNNs). Ho...
- A Deep Neural Network Based on Prior-Driven and Structural Preserving for SAR Image Despeckling
- IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSINGLin, Cong Qiu, Chenghao Jiang, Haoyu Zou, Lilan 出版年：2023
- Remarkable effectiveness has been demonstrated by deep neural networks in the despeckling task for synthetic aperture radar (SAR) images. However, blurring and loss of fine details can result from many despeckling models...
- A Two-Stage Algorithm for the Detection and Removal of Random-Valued Impulse Noise Based on Local Similarity
- IEEE ACCESSLin, Cong Li, Yuchun Feng, Siling Huang, Mengxing 出版年：2020
- A two-stage denoising algorithm based on local similarity is proposed to process lowly and moderate corrupted images with random-valued impulse noise in this paper. In the noise detection stage, the pixel to be detected ...
- Automatic segmentation of prostate MRI based on 3D pyramid pooling Unet
- MEDICAL PHYSICSLi, Yuchun Lin, Cong Zhang, Yu Feng, Siling Huang, Mengxing Bai, Zhiming 出版年：2023
- PurposeAutomatic segmentation of prostate magnetic resonance (MR) images is crucial for the diagnosis, evaluation, and prognosis of prostate diseases (including prostate cancer). In recent years, the mainstream segmentat...
- CXR-RefineDet: Single-Shot Refinement Neural Network for Chest X-Ray Radiograph Based on Multiple Lesions Detection
- JOURNAL OF HEALTHCARE ENGINEERINGLin, Cong Zheng, Yongbin Xiao, Xiuchun Lin, Jialun 出版年：2022
- The workload of radiologists has dramatically increased in the context of the COVID-19 pandemic, causing misdiagnosis and missed diagnosis of diseases. The use of artificial intelligence technology can assist doctors in ...
- A Shadow Capture Deep Neural Network for Underwater Forward-Looking Sonar Image Detection
- MOBILE INFORMATION SYSTEMSXiao, Taowen Cai, Zijian Lin, Cong Chen, Qiong 出版年：2021
- Image sonar is a widely used wireless communication technology for detecting underwater objects, but the detection process often leads to increased difficulty in object identification due to the lack of equipment resolut...
- Lesion detection of chest X-Ray based on scalable attention residual CNN
- MATHEMATICAL BIOSCIENCES AND ENGINEERINGLin, Cong Huang, Yiquan Wang, Wenling Feng, Siling Huang, Mengxing 出版年：2023
- Most of the research on disease recognition in chest X-rays is limited to segmentation and classification, but the problem of inaccurate recognition in edges and small parts makes doctors spend more time making judgments...
- Multi-Objective Optimization of HEV Transmission System Parameters Based on Immune Genetic Algorithm
- 2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION PROBLEM-SOLVING (ICCP)Tan Guangxing Lin Cong Bai Yuhe Chen Zan 出版年：2015
- In consideration of transmission system parameters impact on fuel economy and exhaust emissions of hybrid electric vehicle ( HEV), a multi-objective optimization scheme, immune genetic algorithm, is proposed in this pape...
- Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network
- CMES-COMPUTER MODELING IN ENGINEERING & SCIENCESZou, Lilan Liang, Bo Cheng, Xu Li, Shufa Lin, Cong 出版年：2023
- Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and mode...
- A dual-path feature reuse multi-scale network for remote sensing image super-resolution
- JOURNAL OF SUPERCOMPUTINGXiao, Huanling Chen, Xintong Luo, Liuhui Lin, Cong 出版年：2025
- Deep neural networks have achieved significant success in the super-resolution of remote sensing images. However, existing deep learning models still suffer from the issue of blurry pseudo-artifacts when restoring high-f...
- A noise level estimation method of impulse noise image based on local similarity
- MULTIMEDIA TOOLS AND APPLICATIONSLin, Cong Ye, Youqiang Feng, Siling Huang, Mengxing 出版年：2022
- The detection and removal methods of impulse noise often need to estimate the noise level of the damaged image in advance to obtain a better detection rate. An effective method of random-value impulse noise level estimat...
- Modified Newton Integration Neural Algorithm for Solving Time-Varying Yang-Baxter-Like Matrix Equation
- NEURAL PROCESSING LETTERSHuang, Haoen Huang, Zifan Wu, Chaomin Jiang, Chengze Fu, Dongyang Lin, Cong 出版年：2023
- This paper intends to solve the time-varying Yang-Baxter-like matrix equation (TVYBLME), which is frequently employed in the fields of scientific computing and engineering applications. Due to its critical and promising ...
- From Semantics to Hierarchy: A Hybrid Euclidean-Tangent-Hyperbolic Space Model for Temporal Knowledge Graph Reasoning
- arXivFeng, Siling Qi, Zhisheng Lin, Cong 出版年：2024
- Temporal knowledge graphs (TKGs) have gained significant attention for thEIr ability to extend traditional knowledge graphs with a temporal dimension, enabling dynamic representation of events over time. TKG reasoning in...
- RNN with High Precision and Noise Immunity:A Robust and Learning-Free Method for Beamforming
- IEEE Internet of Things JournalLin, Cong Jiang, Zhihui Cong, Jingyu Zou, Lilan 出版年：2025
- Recurrent Neural Networks (RNNs), recognized for thEIr high accuracy and strong robustness. However, the adoption of RNN-based solutions for array signal beamforming is still in its infancy, as RNNs are very sensitive to...
- PTE: Prompt tuning with ensemble verbalizers
- EXPERT SYSTEMS WITH APPLICATIONSLiang, Liheng Wang, Guancheng Lin, Cong Feng, Zhuowen 出版年：2025
- Prompt tuning has achieved remarkable success in facilitating the performance of Pre-trained Language Models (PLMs) across various downstream NLP tasks, particularly in scenarios with limited downstream data. Reframing t...
- Solving Perturbed Time-Varying Linear Equation and Inequality Problem With Adaptive Enhanced and Noise Suppressing Zeroing Neural Network
- IEEE ACCESSWu, Chaomin Huang, Zifan Wu, Jiahao Lin, Cong 出版年：2022
- Solving time-varying linear equation and inequality (TVLEI) problem has attracted extensive attention in numerous scientific and engineered fields. In this article, it is basically considered that the commonly used dynam...
- A Deep Neural Network Based on Circular Representation for Target Detection
- JOURNAL OF SENSORSLin, Cong Chen, Zhoujian Huang, Yiquan Jiang, Haoyu Du, Wencai Chen, Qiong 出版年：2022
- Convolutional neural network (CNN) model based on deep learning has excellent performance for target detection. However, the detection effect is poor when the object is circular or tubular because most of the existing ob...
- A despeckling method for ultrasound images utilizing content-aware prior and attention-driven techniques
- Computers in Biology and MedicineQiu, Chenghao Huang, Zifan Lin, Cong Zhang, Guodao Ying, Shenpeng 出版年：2023
- The despeckling of ultrasound images contributes to the enhancement of image quality and facilitates precise treatment of conditions such as tumor cancers. However, the use of existing methods for eliminating speckle noi...
- Advancing regional heat load forecasting through sophisticated data-driven methodologies integrated with robust adversarial training strategies
- JOURNAL OF BUILDING ENGINEERINGZhu, Haoran Cheng, Xu Liu, Xiufeng Lin, Cong 出版年：2025
- Facing the severe challenges of global climate change and the continuous growth of building energy consumption, improving the accuracy and robustness of the prediction of district heating systems has become critical to a...
- Adaptive Noise Detector and Partition Filter for Removing Impulse Noise from Grayscale Images
- SSRNLin, Cong Qiu, Chenghao Xiao, Xiuchun Feng, Siling Feng, Mengxing 出版年：2022
- The random-value impulse noise (RVIN) denoising method based on the preset detection threshold or local window information does not have good generalization performance and edge-preserving denoising effect. In this paper...
