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Claim this profileWorks139 from public data
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- Recent progress on vascular endothelial growth factor receptor inhibitors with dual targeting capabilities for tumor therapy210
An overview of the development of VEGFR dual-target inhibitors from multiple aspects, including rational target combinations, drug discovery strategies, structure–activity relationships and future directions is provided.
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- Iterative identification of Hammerstein systems181
The iterative method was first proposed to estimate Hammerstein system in [9] and the results are extended to Hammerstein systems with an IIR linear part, where the global convergence for a IIR system is established for the odd nonlinearities.
- Perceiving and Modeling Density for Image Dehazing156
A novel Separable Hybrid Attention (SHA) module is proposed to perceive haze density by capturing positional-sensitive features in the orthogonal directions to achieve this goal and a density encoding matrix is proposed to model the uneven distribution of the haze explicitly.
- NightHazeFormer: Single Nighttime Haze Removal Using Prior Query Transformer143
Extensive experiments on several synthetic and real-world datasets demonstrate the superiority of the NightHazeFormer over state-of-the-art nighttime haze removal methods in terms of both visually and quantitatively.
- Al-Doped MoSe2 Monolayer as a Promising Biosensor for Exhaled Breath Analysis: A DFT Study131
Al-doped MoSe2 (Al–MoSe2) is proposed as a promising biosensor for sensing three typically exhaled volatile organic compounds (VOCs) of lung cancer, namely, C3H4O,C3H6O, and C5H8, using the density functional theory (DFT) method.
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- MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing88
A multi-scale projection transformer (MSP-Former), which understands and covers a variety of snow degradation features in a multi-path manner, and integrates comprehensive scene context information for clean reconstruction via self-attention operation, achieves the SOTA performance on three desnowing benchmark datasets while costing the low parameters and computational complexity.
- HFS: Hierarchical Feature Selection for Efficient Image Segmentation69
This paper proposes a real-time system, Hierarchical Feature Selection (HFS), that performs image segmentation at a speed of 50 frames-per-second, and can be used in a variety computer vision tasks that are built on top ofimage segmentation and superpixel extraction.
- Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement68
Thorough extensive experiments and comprehensive visual comparison, it is shown that FA$^{+}$Net outperforms previous approaches by obtaining state-of-the-art performance on multiple datasets while significantly reducing both parameter count and computational complexity.
- Underwater Light Field Retention : Neural Rendering for Underwater Imaging68
UWNR is a data-driven neural network that implicitly learns the natural degenerated model from authentic underwater images, avoiding introducing erroneous biases by hand-craft imaging models and is able to synthesize a wide variety of underwater images from one clean image with various realistic underwater images.
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- Single Image Dehazing via Large Sky Region Segmentation and Multiscale Opening Dark Channel Model64
Experimental results on different kinds of hazy images indicate that the proposed approach can produce the visually desirable results with genuine color and high scene visibility, even superior than the other state-of-the-art dehazing methods.
- SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowing55
A powerful architecture dubbed as SnowFormer performs Scale-aware Feature Aggregation in the encoder to capture rich snow information of various degradations and uses a novel Context Interaction Trans-former Block in the decoder in order to tackle with large-scale degradation.
- Discovery of 4-Hydroxyquinazoline Derivatives as Small Molecular BET/PARP1 Inhibitors That Induce Defective Homologous Recombination and Lead to Synthetic Lethality for Triple-Negative Breast Cancer Therapy54
This strategy aims to expand the use of PARPi in BRCA-competent TNBC, making an innovative approach to address unmet oncology needs and optimized the BRD4-PARP1 inhibitor based on previous studies.
- Trajectory Planning Algorithm of UAV Based on System Positioning Accuracy Constraints52
The improved genetic algorithm (GA) and A* algorithm are used in trajectory planning to ensure the UAV has the shortest trajectory length from the starting point to the ending point under multiple constraints and the least number of error corrections.
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- A Unified Variational Model for Single Image Dehazing40
A simple but effective unified variational model for single image dehazing is presented based on the total variation regularization, which can simultaneously obtain the accurate transmission map and the recovered scene radiance by integrating the transmission estimation stage and the image recovery stage into the unified Variational model.
- Deep Residual Convolutional Neural Network for Hyperspectral Image Super-Resolution37
A deep residual convolutional neural network is proposed to increase the spatial resolution of hyperspectral image by minimizing the difference between the estimated image and the ground truth high resolution image.
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- RGB-D Indiscernible Object Counting in Underwater Scenes21
IOCFormer is proposed, a new strong baseline that combines density and regression branches in a unified framework and can effectively tackle object counting under concealed scenes and IOCFormer-D is proposed to enable the effective usage of depth modality to help count objects hidden in their environments.
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- SnowMaster: Comprehensive Real-world Image Desnowing via MLLM with Multi-Model Feedback Optimization19
- Uncertainty-Driven Dynamic Degradation Perceiving and Background Modeling for Efficient Single Image Desnowing19
This paper proposes Dynamic Perceiving for Degraded Regions and Axial-Pooling Attention for Background Structure Modeling, which together couple a new network architecture, dubbed as D2P-BMNet, which significantly improves over prior methods across all benchmarks and maintains excellent inference speeds.
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- DEHRFormer: Real-Time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes18
A real-time transformer for simultaneous single image Depth Estimation and Haze Removal (DEHRFormer) and a novel learning paradigm that utilizes contrastive learning and domain consistency learning to tackle weak-generalization problem for real-world dehazing.
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- CPLFormer: Cross-scale Prototype Learning Transformer for Image Snow Removal17
This work proposes a novel approach, CPLFormer, which uses snow prototypes to own comprehensive clean scene understanding through learning from cross-scale features, outperforming convolutional network and vanilla transformer-based solutions.
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- Sequential Affinity Learning for Video Restoration10
The proposed Sequential Affinity Learning Network (SALN), a novel approach for video restoration that eliminates inefficient temporal modeling operators and pixel-level feature alignment in the network architecture, is designed based on an affinity mechanism that establishes direct correspondences between the Query frame, degraded sequence, and restored frames in latent space.
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- Towards Efficient Single Image Dehazing and Desnowing7
An efficient and compact image restoration network named DAN-Net (Degradation-Adaptive Neural Network) to address the problem of removing adverse weather conditions from images, which consists of multiple compact expert networks with one adaptive gated neural.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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