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Found 10 papers, 1 papers with code
Improved Dense Nested Attention Network Based on Transformer for Infrared Small Target Detection
To address this issue, we propose a novel method for detecting infrared small targets called improved dense nested attention network (IDNANet), which is based on the transformer architecture.
Flexible uniform-sampling foveated Fourier single-pixel imaging
At a sampling ratio of 0. 0084 referring to HR FSI with 1024*768 pixels, experimentally, by UFFSI with 255*341 cells of 89% reduction in data redundancy, the ROI has a significantly better imaging quality to meet imaging needs.
Rega-Net:Retina Gabor Attention for Deep Convolutional Neural Networks
Extensive research works demonstrate that the attention mechanism in convolutional neural networks (CNNs) effectively improves accuracy.
Temporally and Spatially variant-resolution illumination patterns in computational ghost imaging
For the same number of measurements, the method using temporally variable-resolution illumination patterns has better imaging quality than CGI, but it is less robust to noise.
Pose correction scheme for camera-scanning Fourier ptychography based on camera calibration and homography transform
Fourier ptychography (FP), as a computational imaging method, is a powerful tool to improve imaging resolution.
Parallel Fourier Ptychography reconstruction
Fourier ptychography has attracted a wide range of focus for its ability of large space-bandwidth-produce, and quantative phase measurement.
Window Filtering Algorithm for Pulsed Light Coherent Combining of Low Repetition Frequency
The multi-dithering method has been well verified in phase locking of polarization coherent combination experiment.
Optimization of retina-like illumination patterns in ghost imaging
This proposed method is verified by simulations and experiments compared with conventional GI, retina-like GI and GI using patterns optimized by principal component analysis.
Complementary Fourier single-pixel imaging
The complementary nature of Fourier patterns based on a four-step phase-shift algorithm is combined with the complementary nature of a digital micromirror device.
An Effective Training Method For Deep Convolutional Neural Network
In this paper, we propose the nonlinearity generation method to speed up and stabilize the training of deep convolutional neural networks.
