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Maize Kernel Batch Counting System Based on YOLOv8-ByteTrack. [PDF]

Sensors (Basel)
Li R, Liu Q, Wang M, Su Y, Li C, Ou M, Liu L.   +6 more
europepmc   +1 more source

Enhanced YOLOv8 for accurate and efficient floating object detection on water surfaces. [PDF]

Sci Rep
Cao Y, Luo H, Wang M, Wang Y, Yan H.
europepmc   +1 more source

Blur Kernel Estimation by Using Bees Algorithm

, 2016
openaire   +2 more sources

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Blur-Kernel Bound Estimation From Pyramid Statistics

IEEE Transactions on Circuits and Systems for Video Technology, 2016
This letter presents an approach for automatically estimating the spatial bound of the blur kernel in a motion-blurred image based on the statistics of multilevel image gradients. We observe that blur has a significant impact on the histogram of oriented gradients (HOGs) at higher levels of an image pyramid, but has much less of an impact at coarser ...
Shaoguo Liu, Haibo Wang, Jue Wang, Chunhong Pan   +3 more
semanticscholar   +4 more sources

Explore Image Deblurring via Encoded Blur Kernel Space

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
This paper introduces a method to encode the blur operators of an arbitrary dataset of sharp-blur image pairs into a blur kernel space. Assuming the encoded kernel space is close enough to in-the-wild blur operators, we propose an alternating optimization algorithm for blind image deblurring.
Phong Tran, Anh Tuan Tran, Quynh Phung, Minh Hoai   +3 more
openaire   +2 more sources

A Nonblind Deconvolution Method by Bias Correction for Inaccurate Blur Kernel Estimation in Image Deblurring

IEEE Transactions on Geoscience and Remote Sensing, 2023
The blur kernel estimated by a blind deblurring algorithm is hardly to be error-free. The blur kernel error is usually ignored in the nonblind deconvolution stage and may result in severe artifacts or other negative effects.
Jie Han, Songlin Zhang, Z. Ye
semanticscholar   +3 more sources

Unsupervised Blur Kernel Learning for Pansharpening

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020
Deep learning (DL) for pansharpening has recently attracted considerable attentions. To construct training data, DL based pansharpening approaches often downsample the original multispectral image (MSI) and panchromatic image (PAN) with fixed blur kernel, which can be different from the real point spread functions (PSF) of the satellites.
Anjing Guo, Renwei Dian, Shutao Li
openaire   +2 more sources

Joint blur kernel estimation and CNN for blind image restoration

Neurocomputing, 2020
Convolutional neural networks (CNN) have shown its excellent performance in computer vision fields. Recently, they are successfully applied to image restoration.
Liqin Huang, Youshen Xia
semanticscholar   +3 more sources