• Title/Summary/Keyword: Soft filters

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Consideration of CCD Gate Structure in the Determination of the Point Spread Function of Yohkoh Soft X-Ray Telescope (SXT)

  • Shin, Jun-Ho;Sakurai, Takashi
    • The Bulletin of The Korean Astronomical Society
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    • v.37 no.1
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    • pp.93.2-93.2
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    • 2012
  • Point Spread Function (PSF) is one of the most important optical characteristics for describing the performance of a telescope. And a concept of subpixelization is inevitable in evaluating the undersampled PSF (Shin and Sakurai 2009). Then, the internal structure of Yohkoh SXT CCD pixel is not uniform: For the top half of pixel area, the X-ray should pass a so-called gate structure where the charges are transferred to an output amplifier. This gate structure shows energy-dependent sensitivity (Tsuneta et al. 1991). For example, for Al-K (8.34 A) X-ray emission, the transmission of the polysilicon gate is about 0.9. Also, for the peak coronal response of the SXT thin filters, around 17 angstrom (0.729 keV), the transmission of the gate is about 0.6, falling off sharply towards longer wavelengths. It should be noted that this spectrally dependent non-uniform response of each CCD pixel will certainly have a noticeable effect on the properties of the PSF at longer wavelengths. Therefore, especially for analyzing the undersampled PSF of low energy source, a careful consideration of non-uniform internal pixel structure is required in determining the shape of the PSF core. The details on the effect of gate structure will be introduced in our presentation.

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A method based on Multi-Convolution layers Joint and Generative Adversarial Networks for Vehicle Detection

  • Han, Guang;Su, Jinpeng;Zhang, Chengwei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.1795-1811
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    • 2019
  • In order to achieve rapid and accurate detection of vehicle objects in complex traffic conditions, we propose a novel vehicle detection method. Firstly, more contextual and small-object vehicle information can be obtained by our Joint Feature Network (JFN). Secondly, our Evolved Region Proposal Network (EPRN) generates initial anchor boxes by adding an improved version of the region proposal network in this network, and at the same time filters out a large number of false vehicle boxes by soft-Non Maximum Suppression (NMS). Then, our Mask Network (MaskN) generates an example that includes the vehicle occlusion, the generator and discriminator can learn from each other in order to further improve the vehicle object detection capability. Finally, these candidate vehicle detection boxes are optimized to obtain the final vehicle detection boxes by the Fine-Tuning Network(FTN). Through the evaluation experiment on the DETRAC benchmark dataset, we find that in terms of mAP, our method exceeds Faster-RCNN by 11.15%, YOLO by 11.88%, and EB by 1.64%. Besides, our algorithm also has achieved top2 comaring with MS-CNN, YOLO-v3, RefineNet, RetinaNet, Faster-rcnn, DSSD and YOLO-v2 of vehicle category in KITTI dataset.

A Novel Self-Learning Filters for Automatic Modulation Classification Based on Deep Residual Shrinking Networks

  • Ming Li;Xiaolin Zhang;Rongchen Sun;Zengmao Chen;Chenghao Liu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.6
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    • pp.1743-1758
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    • 2023
  • Automatic modulation classification is a critical algorithm for non-cooperative communication systems. This paper addresses the challenging problem of closed-set and open-set signal modulation classification in complex channels. We propose a novel approach that incorporates a self-learning filter and center-loss in Deep Residual Shrinking Networks (DRSN) for closed-set modulation classification, and the Opendistance method for open-set modulation classification. Our approach achieves better performance than existing methods in both closed-set and open-set recognition. In closed-set recognition, the self-learning filter and center-loss combination improves recognition performance, with a maximum accuracy of over 92.18%. In open-set recognition, the use of a self-learning filter and center-loss provide an effective feature vector for open-set recognition, and the Opendistance method outperforms SoftMax and OpenMax in F1 scores and mean average accuracy under high openness. Overall, our proposed approach demonstrates promising results for automatic modulation classification, providing better performance in non-cooperative communication systems.

Reduction of Electron Contamination Using a Filter for 6MV Photon Beam (6MV 광자선에서 전자오염 감소에 관한 연구)

  • Lee, Choul-Soo;Yoo, Myung-Jin;Yum, Ha-Yong
    • Radiation Oncology Journal
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    • v.15 no.2
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    • pp.159-165
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    • 1997
  • Purpose : Secondary electrons generated by interaction between Primary X-rar beam and block tray in megavoltage irradiation, result in excess soft radiation dose to the surface layer To reduce the surface dose from the electron contamination, electron filters were attached under the tray when a customized block was used. Materials and Methods : Cu, Al or Cu/Al combined Plate with different thickness was used as a filter and the surface dose reduction was measured for each case. The measurement to find optimal filter was performed with $10m\times10cm$ field size and 78.5cm source to surface distance. The measurement points are positioned with 2mm intervals from surface to maximum build-up point. To acquire the effect of field size dependence on optimal electron filter, the measurement was performed from $4cm\times4cm\;to\;25cm\times25cm$ field sizes. Results : The surface dose was slowly increased by increasing irradiation field but rapidly increased beyond $15cm\times15cm$ field size. Al plate was found to be inadequate filter because of the failure to have surface dose kept lowering than the dose of deep area. Cu 0.5mm plate and Cu/Al=0.28mm/1.5mm combined plate were found to be optimal filters. By using these 2 filters, the absorbed dose to the surface layer was effectively reduced by $5.5\%,\;11.3\%,\;and\;22.3\%$ for the field size $4cm\times4cm,\;10m\times10cm,\;and\;25cm\times25cm$, respectively. Conclusion : The surface dose attributable to electron contamination had a dependence on field size. The electron contamination was increased when tray was used. Specially the electron contamination in the surface layer was greater when the larger field was used. 0.5mm Cu Plate and Cu/Al=0.28mm/15mm combined plates were selected as optimal electron filters. When the optimal electron filter was attached under the tray, excessive surface dose was decreased effectively The effect of these electron filters was better when a larger field was used.

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A Study on the Generation of Ultrasonic Binary Image for Image Segmentation (Image segmentation을 위한 초음파 이진 영상 생성에 관한 연구)

  • Choe, Heung-Ho;Yuk, In-Su
    • Journal of Biomedical Engineering Research
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    • v.19 no.6
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    • pp.571-575
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    • 1998
  • One of the most significant features of diagnostic ultrasonic instruments is to provide real time information of the soft tissues movements. Echocardiogram has been widely used for diagnosis of heart diseases since it is able to show real time images of heart valves and walls. However, the currently used ultrasonic images are deteriorated due to presence of speckle noises and image dropout. Therefore, it is very important to develop a new technique which can enhance ultrasonic images. In this study, a technique which extracts enhanced binary images in echocardiograms was proposed. For this purpose, a digital moving image file was made from analog echocardiogram, then it was stored as 8-bit gray-level for each frame. For an efficient image processing, the region containing the heat septum and tricuspid valve was selected as the region of interest(ROI). Image enhancement filters and morphology filters were used to reduce speckle noises in the images. The proposed procedure in this paper resulted in binary images with enhanced contour compared to those form the conventional threshold technique and original image processing technique which can be further implemented for the quantitative analysis of the left ventricular wall motion in echocardiogram by easy detection of the heart wall contours.

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