2023
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Record 1 of 10 | ||||||
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Title: Imaging Linearity Modeling and Optimization of Capacitive Division Image Readout (C-DIR) for Microchannel Plate Imaging Detectors | ||||||
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Author(s): Yang, K (Yang, Kai); Bai, YL (Bai, Yonglin); Zhu, BL (Zhu, Bingli); Wang, B (Wang, Bo); Cao, WW (Cao, Weiwei); Zhang, SD (Zhang, Shengdan); Bai, XH (Bai, Xiaohong); Zheng, JK (Zheng, Jinkun); Yang, Y (Yang, Yang); Chen, Z (Chen, Zhen) | ||||||
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Source: IEEE TRANSACTIONS ON NUCLEAR SCIENCE Volume: 70 Issue: 7 Pages: 1497-1506 DOI: 10.1109/TNS.2023.3265720 Published: JUL 2023 | ||||||
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Abstract: A 3-D lumped parameter circuit model based on the nodal analysis to simulate signal propagation and position response characteristics of capacitive division image readout (C-DIR) is proposed. The current pulses, charge collection efficiency, and position reconstruction patterns are calculated for different electrical parameters (charge division capacitor C-c, perimeter capacitor C-p, diagonal capacitor C-d, electrode parasitic capacitor C-s, and the sheet resistance of the resistive layer R-Ge), and their influence on imaging linearity is investigated. The simulation results show that R-Ge affects the amplitude, pulsewidth, and polarity of the current pulse in the C-DIR. The sheet resistance of the resistive layer needs to be larger than 10 MQ for the charge to be efficiently collected by the readout electronics. Several capacitance ratios (C-c/C-p, C-c/C-s, and C-c/C-d) mainly affect the imaging linearity. It has been found that to obtain good detector imaging performance, C-c/C-p should be less than 0.01, C-c/C-s should be larger than 100, and C-c/C-d should be larger than 10, and when RGe is larger than 10 Mg, the imaging nonlinearity (rms) can be less than 1%. The reliability of the simulation results was verified by experimental measurements of a prototype C-DIR detector designed by ourselves. An optimized imaging performance with imaging nonlinearity (rms) of 2.18% was achieved. | ||||||
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Accession Number: WOS:001033559700034 | ||||||
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Conference Title: 16th INTERNATIONAL CONFERENCE ON INORGANIC SCINTILLATORS AND THEIR APPLICATIONS (SCINT) | ||||||
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Conference Date: SEP 19-OCT 23, 2022 | ||||||
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Conference Location: Santa Fe, NM | ||||||
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ISSN: 0018-9499 | ||||||
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eISSN: 1558-1578 |
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Record 2 of 10 | ||||||
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Title: A Sparse Sampling Method in the Two-dimensional Spatial Domain for Sheared-beam Imaging Receiving System | ||||||
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Author(s): Chen, ML (Chen, Minglai); Ma, CW (Ma, Caiwen); Luo, XJ (Luo, Xiujuan); Liu, H (Liu, Hui); Zhang, Y (Zhang, Yu); Yue, ZL (Yue, Zelin); Zhao, J (Zhao, Jing) | ||||||
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Edited by: Liu X; Zayats A; Yuan X | ||||||
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Source: SPIE-CLP CONFERENCE ON ADVANCED PHOTONICS 2022 Book Series: Proceedings of SPIE Volume: 12601 Article Number: 126010M DOI: 10.1117/12.2666901 Published: 2023 | ||||||
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Abstract: In the imaging of low-orbit moving objects, the number of detector elements in the traditional sheared-beam imaging (SBI) system is too great, which seriously restrict the application of SBI. In this paper, the detector array is sparse in two dimensions. We propose a two-dimensional sparse sampling imaging method, which emits a two-dimensional coherent laser array, carries more spectral information of the target at a time and receives speckle echo signals by a two-dimensional sparse detector array for computational imaging. This method can reduce the number of detector elements many times. Firstly, the principle of two-dimensional sparse sampling with SBI detector array is deduced theoretically. Secondly, a two-dimensional spatial sparse reconstruction algorithm is investigated. The target amplitude product and phase difference carried by each detector array element is estimated using discrete Fourier transform, then the target amplitude product and phase difference of all detector array elements are matched respectively to form a complete target amplitude product surface and phase difference surface. The formulas of phase recovery and amplitude demodulation are derived. Finally, the validity and feasibility of the proposed method are verified by simulation. Compared with the traditional three-beam method, when the number of lasers in emission array is MxN, the number of detector elements is reduced to 1/(M-1)/(N-1) of the original without loss of imaging resolution. | ||||||
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Accession Number: WOS:001058150400020 | ||||||
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Conference Title: SPIE-CLP Conference on Advanced Photonics | ||||||
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Conference Date: NOV 21-24, 2022 | ||||||
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Conference Location: ELECTR NETWORK | ||||||
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Conference Sponsors: SPIE, Chinese Laser Press, Zhejiang Lab | ||||||
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Author Identifiers: | ||||||
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ISSN: 0277-786X | ||||||
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eISSN: 1996-756X | ||||||
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ISBN: 978-1-5106-6328-2; 978-1-5106-6329-9 |
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Record 3 of 10 | ||||||
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Title: A Hybrid Mathematical Models for Predicting Global Climate Change | ||||||
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Author(s): Chen, TY (Chen, Taoyue); Zhang, ZY (Zhang, Zhaoyue); Yi, ZL (Yi, Zilu); Xu, WX (Xu, Wenxi); Yang, K (Yang, Kai) | ||||||
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Book Group Author(s): IEEE | ||||||
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Source: 2023 3RD ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE, ACCTCS Pages: 357-367 DOI: 10.1109/ACCTCS58815.2023.00052 Published: 2023 | ||||||
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Abstract: The industrial revolution marked the beginning of modernization in human civilization, and also marked the sharp rise in greenhouse gas emissions and global temperatures. To better understand trends in global climate change, we aim to utilize data on carbon dioxide levels and land-ocean temperatures to learn past trends and predict future changes. First, the CO2 concentration dataset, using statistical methods, is analyzed and visualized. From the statistical summary and graphs, it can be concluded that the global CO2 level has been constantly increasing since the 1960s. Based on the dataset, three models were constructed to analyze the changing trend of CO2 levels in the past and extrapolate the future: Autoregressive Integrated Moving Average (ARIMA), grey forecast, and a more refined prediction model that considers factors affecting CO2 levels with Long Short Term Memory (LSTM). All three models disagree that the CO2 level will reach 685 PPM by 2050. And each model predicts CO2 level of 685 PPM will be reached by the end of the century and when. Afterward, the pros and cons of the models are compared. Second, the model of the changes in global land-ocean temperature is constructed. ARIMA is used to model and predict the upcoming temperature and the time when it is going to reach certain designated points. Pearson's correlation shows a strong correlation between global temperature and CO2 level. Hence, these two variables are modeled with linear regression. However, the regression-based predictions did not match the forecast from earlier models, so an refined model incorporating more variables and perspectives was built. The refined model is a more bottom-up approach. It quantifies the radiative forcing of individual factors and makes predictions based on the predicted outcomes of each factor. The model predicts the temperature difference of 3.55 degrees C from the base period, 1.25 degrees C in 2031, 1.5 degrees C in 2039, and 2 degrees C in 2052. | ||||||
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Accession Number: WOS:001031393400066 | ||||||
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Conference Title: 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) | ||||||
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Conference Date: FEB 25-27, 2023 | ||||||
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Conference Location: Shenyang, PEOPLES R CHINA | ||||||
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Author Identifiers: | ||||||
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ISBN: 979-8-3503-1080-1 |
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Record 4 of 10 | |||||||||
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Title: Enhancing the Quantum Correlation of Biphotons via Coherent Energy Redistribution | |||||||||
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Author(s): Crockett, B (Crockett, Benjamin); Montaut, N (Montaut, Nicola); van Howe, J (van Howe, James); Roztocki, P (Roztocki, Piotr); Liu, Y (Liu, Yang); Helsten, R (Helsten, Robin); Zhao, W (Zhao, Wei); Morandotti, R (Morandotti, Roberto); Aza?a, J (Azana, Jose) | |||||||||
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Book Group Author(s): IEEE | |||||||||
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Source: 2023 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION, OFC DOI: 10.1364/OFC.2023.Th3J.6 Published: 2023 | |||||||||
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Abstract: Towards meeting the strict demands of practical quantum networks, we leverage coherent energy redistribution for noise -tolerant quantum signal processing. We demonstrate the enhancement of noisy biphoton coincidence -to -accidental ratios by up to 3.8 times. (c) 2022 The Author(s) | |||||||||
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Accession Number: WOS:001009232500470 | |||||||||
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Conference Title: Optical Fiber Communications Conference and Exhibition (OFC) | |||||||||
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Conference Date: MAR 05-09, 2023 | |||||||||
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Conference Location: San Diego, CA | |||||||||
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Conference Sponsors: IEEE, Acacia Commun Inc, Acphotonics, Amphenol, Ciena, Cisco, Corning, Dimensiion, Hyc Co Ltd, Infinera, Ligentec, Marvell, Olf, Ozoptics, Santec, Sanwa Technologies, Senko Adv Components, Sheetak, Sumitomo Elect Lightwave, Synopsys, USConec, VPIPhotonics | |||||||||
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ISBN: 978-1-957171-18-0 |
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Record 5 of 10 | ||||||
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Title: A Model of Honeybee Population Dynamics and Pollination Prediction | ||||||
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Author(s): Jing, KF (Jing, Kaifeng); Liu, ZP (Liu, Zhenpeng); Liu, ZH (Liu, Zihan); Yang, JT (Yang, Jingtong); Yang, K (Yang, Kai) | ||||||
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Book Group Author(s): IEEE | ||||||
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Source: 2023 3RD ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE, ACCTCS Pages: 335-342 DOI: 10.1109/ACCTCS58815.2023.00051 Published: 2023 | ||||||
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Abstract: Honeybee population dynamics and prediction is the core content of honeybee population ecology research, which is closely related to the development of agriculture, economy and other industries. This paper aims to study honeybee population dynamics and pollination prediction. Firstly, a differential equation model is proposed to analyze the number of bees in a single beehive in detail, and the Elman model is used to further validate it. Then, through a sensitivity analysis of bee colony size, the main factors affecting hive colony size were identified: the egg-laying rate and the number of varroa mites. Furthermore, combined with the differential equation model, a beehive prediction model for crop pollination was constructed, which can predict the number of beehives required for crop pollination on a 20-acre (81,000) land. At the same time, the effect of initial beehive colony size on the number of beehives required for pollination of different plants in a given area was studied in depth. The usefulness and applicability of our model is well demonstrated by the reasonable trend and prediction results of colony size obtained by applying the model to real data. Finally, the paper provides an outlook on future research and improvement directions in this field. | ||||||
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Accession Number: WOS:001031393400062 | ||||||
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Conference Title: 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) | ||||||
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Conference Date: FEB 25-27, 2023 | ||||||
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Conference Location: Shenyang, PEOPLES R CHINA | ||||||
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Author Identifiers: | ||||||
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ISBN: 979-8-3503-1080-1 |
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Record 6 of 10 |
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Title: Construction of Vehicle Driving Cycle Based on Markov Model |
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Author(s): Liu, PX (Liu, Panxiong); Yang, K (Yang, Kai); Li, XJ (Li, Xijie) |
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Book Group Author(s): IEEE |
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Source: 2023 3RD ASIA-PACIFIC CONFERENCE ON COMMUNICATIONS TECHNOLOGY AND COMPUTER SCIENCE, ACCTCS Pages: 299-304 DOI: 10.1109/ACCTCS58815.2023.00049 Published: 2023 |
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Abstract: With the continuous development of China's economy, the sales volume of automobiles across the country continues to grow. The vehicle driving cycle describes the vehicle speed time curve, which is used to determine vehicle pollutant emissions, fuel consumption, new model development and evaluation. It is a key basic technology in the automotive industry. Therefore, it is of great significance to carry out research on the driving cycle of vehicles on urban roads in China. Markov model is used to model the vehicle driving cycle in a given city. The average speed, average driving speed, average acceleration, average deceleration, idling time ratio, acceleration time ratio, deceleration time ratio, standard deviation of speed, standard deviation of acceleration and other index values are extracted for each kinematics segment, and these index values are input into the Markov chain to obtain the corresponding vehicle driving condition data. At the same time, the comprehensive evaluation system is constructed based on the calculated index values. We use the entropy weight method combined with the gray evaluation model to evaluate the vehicle driving cycle model. The evaluation results show that the Markov model of vehicle driving cycle proposed by us has a good effect. |
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Accession Number: WOS:001031393400055 |
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Conference Title: 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS) |
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Conference Date: FEB 25-27, 2023 |
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Conference Location: Shenyang, PEOPLES R CHINA |
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ISBN: 979-8-3503-1080-1 |
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Record 7 of 10 |
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Title: Classification of skin cancer based on hyperspectral microscopic imaging and machine learning |
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Author(s): Qia, MJ (Qia, Meijie); Liu, YJ (Liu, Yujie); Li, YR (Li, Yanru); Liu, LX (Liu, Lixin); Zhang, ZF (Zhang, Zhoufeng) |
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Edited by: Liu X; Zayats A; Yuan X |
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Source: SPIE-CLP CONFERENCE ON ADVANCED PHOTONICS 2022 Book Series: Proceedings of SPIE Volume: 12601 Article Number: 1260103 DOI: 10.1117/12.2666425 Published: 2023 |
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Abstract: Hyperspectral microscopic imaging (HMI) technology is a non-contact optical diagnostic method, which combines hyperspectral imaging (HSI) technology with microscopy to provide both spectral information and image information of the samples to be measured. In this paper, basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and malignant melanoma (MM) were classified based on synthetic RGB image data from HMI cube by using four classification methods extreme learning machine (ELM), support vector machine (SVM), decision tree and random forest (RF). The highest classification accuracy of 0.791 +/- 0.060 and a KAPPA value of 0.685 +/- 0.095 were obtained when color moment, gray level co-occurrence matrix (GLCM) and local binary pattern (LBP) were used for image feature extraction, feature dimensions were reduced by the PLS, the sample sets were divided by the hold-out method, and the tissues were classified by the SVM model. |
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Accession Number: WOS:001058150400002 |
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Conference Title: SPIE-CLP Conference on Advanced Photonics |
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Conference Date: NOV 21-24, 2022 |
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Conference Location: ELECTR NETWORK |
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Conference Sponsors: SPIE, Chinese Laser Press, Zhejiang Lab |
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ISSN: 0277-786X |
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eISSN: 1996-756X |
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ISBN: 978-1-5106-6328-2; 978-1-5106-6329-9 |
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Record 8 of 10 | ||||||
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Title: Simulating Human Visual System Based on Vision Transformer | ||||||
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Author(s): Qiu, MY (Qiu, Mengyu); Guo, Y (Guo, Yi); Zhang, MG (Zhang, Mingguang); Zhang, JW (Zhang, Jingwei); Lan, T (Lan, Tian); Liu, ZL (Liu, Zhilin) | ||||||
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Edited by: Spencer SN | ||||||
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Source: ACM SYMPOSIUM ON SPATIAL USER INTERACTION, SUI 2023 Article Number: 58 DOI: 10.1145/3607822.3616408 Published: 2023 | ||||||
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Abstract: The human visual system (HVS) is capable of responding in real-time to complex visual environments. During the process of freely observing visual scenes, predicting eye movements and visual fixations is a task known as scanpath prediction, which aims to simulate the HVS. In this paper, we propose a visual transformer-based model to study the attentional processes of the human visual system in analyzing visual scenes, thereby achieving scanpath prediction. This technology has important applications in human-computer interaction, virtual reality, augmented reality, and other fields. We have significantly simplified the workflow of scanpath prediction and the overall model architecture, achieving performance superior to existing methods. | ||||||
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Accession Number: WOS:001138802600058 | ||||||
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Conference Title: 11th ACM Symposium on Spatial User Interaction (SUI) | ||||||
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Conference Date: OCT 13-15, 2023 | ||||||
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Conference Location: Sydney, AUSTRALIA | ||||||
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Conference Sponsors: Assoc Comp Machinery, ACM SIGCHI, ACM SIGGRAPH | ||||||
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Author Identifiers: | ||||||
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ISBN: 979-8-4007-0281-5 |
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Record 9 of 10 |
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Title: Active Interactive Labelling Massive Samples for Object Detection |
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Author(s): Zhang, JW (Zhang, Jingwei); Zhang, MG (Zhang, Mingguang); Guo, Y (Guo, Yi); Qiu, MY (Qiu, Mengyu) |
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Edited by: Spencer SN |
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Source: ACM SYMPOSIUM ON SPATIAL USER INTERACTION, SUI 2023 Article Number: 57 DOI: 10.1145/3607822.3616407 Published: 2023 |
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Abstract: Aerial object detection is the process of detecting objects in remote sensing images, such as aerial or satellite imagery. However, due to the unique characteristics and challenges of remote sensing images, such as large image sizes and dense distribution of small objects, annotating the data is time-consuming and costly. Active learning methods can reduce the cost of labeling data and improve the model's generalization ability by selecting the most informative and representative unlabeled samples. In this paper, we studied how to apply active learning techniques to remote sensing object detection tasks and found that traditional active learning frameworks are not suitable. Therefore, we designed a remote sensing task-oriented active learning framework that can more efficiently select representative samples and improve the performance of remote sensing object detection tasks. In addition, we proposed an adaptive weighting loss to further improve the generalization ability of the model in unlabeled areas. A large number of experiments conducted on the remote sensing dataset DOTA-v2.0 showed that applying various classical active learning methods to the new active learning framework can achieve better performance. |
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Accession Number: WOS:001138802600057 |
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Conference Title: 11th ACM Symposium on Spatial User Interaction (SUI) |
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Conference Date: OCT 13-15, 2023 |
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Conference Location: Sydney, AUSTRALIA |
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Conference Sponsors: Assoc Comp Machinery, ACM SIGCHI, ACM SIGGRAPH |
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ISBN: 979-8-4007-0281-5 |
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Record 10 of 10 |
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Title: Depth of focus extension of space-borne optical camera through variable curvature mirror |
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Author(s): Zhao, H (Zhao Hui); Xie, XP (Xie Xiaopeng); Yang, MY (Yang Mingyang); Zou, GY (Zou Gangyi); Zhang, YT (Zhang Yating); Fan, XW (Fan Xuewu) |
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Edited by: Wang Y; Kidger TE; Wu R |
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Source: OPTICAL DESIGN AND TESTING XIII Book Series: Proceedings of SPIE Volume: 12765 Article Number: 127651H DOI: 10.1117/12.2687237 Published: 2023 |
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Abstract: Currently, most space-borne optical cameras have fixed focal length and depth of focus. In this case, the range within which the target can be clearly imaged has been pre-determined before launch. However, the distance of the target to the optical camera might be unknown or change very fast and therefore focus adjustment has to be carried out to obtain clear images. However, no matter which refocusing technique is used, focus adjustment might lag behind the object distance variation and depth of focus extension is a better way. Wave-front coding can be used to extend the depth of focus of incoherent imaging system but the surface profile of the phase mask could not be changed dynamically, which is not flexible for application. In this manuscript, by combing the variable curvature mirror (VCM) and coded imaging technique together, a new depth of focus extension technique is proposed. According to our previous studies, the focal plane could be quickly adjusted by changing the curvature radius of VCM. Compared with the curvature variation speed, the exposure time of the camera is quite long. Therefore, by adjusting the focal plane very fast in a wide range during the exposure through VCM, an equivalent coded optical transfer function having no null frequency points within bandwidth is generated and the image captured is uniformly blurred. After that, with the help of digital restoration, the clear image could be obtained. Because the focal plane could be adjusted through variable curvature mirror in the range of millimeter, the proposed method could be used to obtain clear images with greatly extended depth of focus. |
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Accession Number: WOS:001147890000041 |
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Conference Title: Conference on Optical Design and Testing XIII |
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Conference Date: OCT 14-15, 2023 |
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Conference Location: Beijing, PEOPLES R CHINA |
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Conference Sponsors: SPIE, Chinese Opt Soc |
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ISSN: 0277-786X |
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eISSN: 1996-756X |
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ISBN: 978-1-5106-6779-2; 978-1-5106-6780-8 |