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2,104 results on '"Tan, Jiubin"'

1. Long working distance portable smartphone microscopy for metallic mesh defect detection

Author

Lu, Zhengang, Qin, Hongsheng, Li, Jing, Sun, Ming, and Tan, Jiubin

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Metallic mesh is a transparent electromagnetic shielding film with a fine metal line structure. However, it can develop defects that affect the optoelectronic performance whether in the production preparation or in actual use. The development of in-situ non-destructive testing (NDT) devices for metallic mesh requires long working distances, reflective optical path design, and miniaturization. To address the limitations of existing smartphone microscopes, which feature short working distances and inadequate transmission imaging for industrial in-situ inspection, we propose a novel long-working distance reflective smartphone microscopy system (LD-RSM). LD-RSM builds a 4f optical imaging system with external optical components and a smartphone, utilizing a beam splitter to achieve reflective imaging with the illumination system and imaging system on the same side of the sample. It achieves an optical resolution of 4.92$\mu$m and a working distance of up to 22.23 mm. Additionally, we introduce a dual prior weighted Robust Principal Component Analysis (DW-RPCA) for defect detection. This approach leverages spectral filter fusion and Hough transform to model different defect types, enhancing the accuracy and efficiency of defect identification. Coupled with an optimized threshold segmentation algorithm, DW-RPCA method achieves a pixel-level accuracy of 84.8%. Our work showcases strong potential for growth in the field of in-situ on-line inspection of industrial products.

Published
2024

4. Being Aware of Localization Accuracy By Generating Predicted-IoU-Guided Quality Scores

Author

Liu, Pengfei, Wang, Weibo, Guo, Yuhan, and Tan, Jiubin

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

Localization Quality Estimation (LQE) helps to improve detection performance as it benefits post processing through jointly considering classification score and localization accuracy. In this perspective, for further leveraging the close relationship between localization accuracy and IoU (Intersection-Over-Union), and for depressing those inconsistent predictions, we designed an elegant LQE branch to acquire localization quality score guided by predicted IoU. Distinctly, for alleviating the inconsistency of classification score and localization quality during training and inference, under which some predictions with low classification scores but high LQE scores will impair the performance, instead of separately and independently setting, we embedded LQE branch into classification branch, producing a joint classification-localization-quality representation. Then a novel one stage detector termed CLQ is proposed. Extensive experiments show that CLQ achieves state-of-the-arts' performance at an accuracy of 47.8 AP and a speed of 11.5 fps with ResNeXt-101 as backbone on COCO test-dev. Finally, we extend CLQ to ATSS, producing a reliable 1.2 AP gain, showing our model's strong adaptability and scalability. Codes are released at https://github.com/PanffeeReal/CLQ.

Published
2023

37. Faster super-resolution imaging with auto-correlation two-step deconvolution

Author

Zhao, Weisong, Liu, Jian, Kong, Chenqi, Zhao, Yixuan, Guo, Changliang, Liu, Chenguang, Ding, Xiangyan, Ding, Xumin, Tan, Jiubin, and Li, Haoyu

Subjects
Physics - Optics
Abstract

Despite super-resolution fluorescence blinking microscopes break the diffraction limit, the intense phototoxic illumination and long-term image sequences thus far still pose to major challenges in visualizing live-organisms. Here, we proposed a super-resolution method based on auto-correlation two-step deconvolution (SACD) to enhance the temporal resolution at lower signal intensity levels. Unlike conventional techniques, such as super-resolution optical fluctuation imaging (SOFI) or stochastic optical reconstruction microscopy (STORM), our model allows 16 frames to generate super-resolution images, without noticeable degradation in recording quality. We demonstrate SACD both in simulated predictions and experimental validations, with the resulting spatial resolution of 64 nm and 2-10 fold speed improvements. The use of low signal-to-noise ratio acquisition of image sequences, our SACD enables fast, background-free, super-resolution imaging that maybe advance implemented as a suitable tool for rapid live-cells imaging., Comment: 13 pages,5 figures

Published
2018

46. Sparse deconvolution improves the resolution of live-cell super-resolution fluorescence microscopy

Author

Zhao, Weisong, Zhao, Shiqun, Li, Liuju, Huang, Xiaoshuai, Xing, Shijia, Zhang, Yulin, Qiu, Guohua, Han, Zhenqian, Shang, Yingxu, Sun, De-en, Shan, Chunyan, Wu, Runlong, Gu, Lusheng, Zhang, Shuwen, Chen, Riwang, Xiao, Jian, Mo, Yanquan, Wang, Jianyong, Ji, Wei, Chen, Xing, Ding, Baoquan, Liu, Yanmei, Mao, Heng, Song, Bao-Liang, Tan, Jiubin, Liu, Jian, Li, Haoyu, and Chen, Liangyi

Published
2022
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