A5061563214- Advanced Image Processing Techniques
- Advanced Vision and Imaging
- Image Processing Techniques and Applications
- Image Enhancement Techniques
- Advanced Image Fusion Techniques
- Infrared Target Detection Methodologies
- Video Surveillance and Tracking Methods
- Domain Adaptation and Few-Shot Learning
- Computer Graphics and Visualization Techniques
- Advanced Image and Video Retrieval Techniques
- Image and Signal Denoising Methods
- Traffic control and management
- Advanced Manufacturing and Logistics Optimization
- Photoacoustic and Ultrasonic Imaging
- Nonlinear Optical Materials Studies
- Nanoplatforms for cancer theranostics
- Advanced Measurement and Detection Methods
- Simulation and Modeling Applications
- Fire Detection and Safety Systems
- Dam Engineering and Safety
- Hydrogels: synthesis, properties, applications
- Optical Coherence Tomography Applications
- Soil, Finite Element Methods
- Artificial Intelligence Applications
- Vehicle Routing Optimization Methods
Zhejiang University
2017-2024
Nanjing University of Aeronautics and Astronautics
2024
Fanjingshan National Nature Reserve
2010-2023
State Key Laboratory of Modern Optical Instruments
2021-2022
Dongguan University of Technology
2021-2022
Louisiana State University
2019-2022
Guidewire (United States)
2022
Cytoskeleton (United States)
2022
Zhejiang University of Technology
2020
Hong Kong Polytechnic University
2019
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. Some existing deep learning based methods are devoted to improving the model performance via increasing depth or width of convolution. The ability Convolutional Neural Network (CNN) structure still under-explored. In this paper, Detail-Enhanced Attention Block (DEAB) consisting Convolution (DEConv) and Content-Guided (CGA) proposed boost feature for performance....
This paper reviewed the 3rd NTIRE challenge on single-image super-resolution (restoration of rich details in a low-resolution image) with focus proposed solutions and results. The had 1 track, which was aimed at real-world single image problem an unknown scaling factor. Participants were mapping images captured by DSLR camera shorter focal length to their high-resolution longer length. With this challenge, we introduced novel dataset (RealSR). track 403 registered participants, 36 teams...
Fixed-pattern noise (FPN), which is caused by the nonuniform opto-electronic responses of microbolometer focal-plane-array (FPA) optoelectronics, imposes a challenging problem in infrared imaging systems. In this paper, we successfully demonstrate that better single-image-based non-uniformity correction (NUC) operator can be directly learned from large number simulated training images instead being handcrafted as before. Our proposed scheme, based on convolutional neural networks (CNNs) and...
Recently, convolutional neural network (CNN) based models have shown great potential in the task of single image superresolution (SISR). However, many state-of-the-art SISR solutions are reproducing some tricks proven effective other vision tasks, such as pursuing a deeper model. In this paper, we propose new solution (named Multi-Receptive-Field Network - MRFN), which outperforms existing three different aspects. First, from receptive field: novel multi-receptive-field (MRF) module is...
Infrared images have a wide range of military and civilian applications, including night vision, surveillance, robotics. However, high-resolution infrared detectors are difficult to fabricate their manufacturing cost is expensive. In this paper, we present cascaded architecture deep neural networks with multiple receptive fields increase the spatial resolution by large scale factor (x8). Instead reconstructing image from its low-resolution version using single complex network, key idea our...
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. Some existing deep learning based methods are devoted to improving the model performance via increasing depth or width of convolution. The ability convolutional neural network (CNN) structure still under-explored. In this paper, detail-enhanced attention block (DEAB) consisting convolution (DEConv) and content-guided (CGA) proposed boost feature for performance....
In this paper we present a novel non-uniformity correction (NUC) method to remove column fixed-pattern noise (FPN), which is introduced by of on-chip column-parallel readout circuit in uncooled infrared focal plane array. We first define new image statistic measurement, named as 1D horizontal differential statistics, differentiate FPN from structural edges, and further propose filtering scheme adaptively compute terms structure non-structure regions applying different models. The proposed...
Recently, Convolutional Neural Network (CNN) based approaches have achieved impressive single image super-resolution (SISR) performance in terms of accuracy and visual effects. It is noted that most SISR methods assume the low-resolution (LR) images are obtained through bicubic interpolation down-sampling, thus their on real-world LR limited. In this paper, we proposed a novel orientation-aware deep neural network (OA-DNN) model, which incorporate number orientation feature extraction...
Mitochondria, key organelles which keep in tune with energy demands for eukaryotic cells, are firmly associated neurological conditions and post-traumatic rehabilitation. In vivo fluorescence imaging of mitochondria, especially deep tissue penetration, would open a window to investigate the actual context brain. However, depth traditional two-photon mitochondrial is still limited due poor biological compatibility or low absorption cross-sections. A biocompatible mitochondria-targeted...
Non-line-of-sight (NLOS) imaging of hidden objects is a challenging yet vital task, facilitating important applications such as rescue operations, medical imaging, and autonomous driving. In this paper, we attempt to develop computational steady-state NLOS localization framework that works accurately robustly under various illumination conditions. For purpose, build physical image acquisition hardware system corresponding virtual setup obtain real-captured simulated images different ambient...
Image Super-Resolution (SR) provides a promising technique to enhance the image quality of low-resolution sensors for wide range optical applications. It is noted that costs capturing high-resolution images in various spectral ranges are significantly different, thus it reasonable utilize low-cost channel (e.g., visible/depth images) as guidance boost accuracy SR results expensive thermal significantly. In this paper, we attempt leverage complementary information from channels...
Digital projectors have been increasingly utilized in various commercial and scientific applications. However, they are prone to the out-of-focus blurring problem since their depth-of-fields typically limited. In this paper, we explore feasibility of utilizing a deep learning-based approach analyze spatially-varying depth-dependent defocus properties digital projectors. A multimodal displaying/imaging system is built for capturing images projected at depths. Based on constructed dataset...
Choristoneura metasequoiacola Liu, 1983 is an important caterpillar species that specifically infests the leaves and branches of Metasequoia glyptostroboides Hu & W. C. Cheng 1948 with short larval infestations, long-term dormancy, has a limited distribution in Lichuan, Hubei, China. The complete mitochondria genome was determined by using Illumina NovaSeq, analyzed based on previously annotated sibling species. In total, we obtained 15,128 bp length, circular shape double-stranded closed...