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检索条件"任意字段=2022 3rd International Conference on Signal Processing and Computer Science, SPCS 2022"

共 761 条记录，以下是31-40 订阅

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Time Difference of Arrival Estimation of Stationary Targets Utilizing Deep Neural Network 3

Time Difference of Arrival Estimation of Stationary Targets ...

引用

2022 3rd international conference on signal processing and computer science, spcs 2022

作者： Xie, Wupeng Liu, Guanghong Xiang, Xiaoxiao Xing, Kang Zhang, Xiaojuan Information Science Academy China Electronics Technology Group Corporation Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China

Time difference of arrival (TDOA) is widely used in the field of passive location because of its flexible base station deployment and simple principle. However, when solving the solution of stationary targets position, the traditional method, such as the two-stage weighted least squares (TSWLS) algorithm, is easily affected by noise, and cannot achieve good localization results in practical situations. To solve this problem, we propose a deep neural network (DNN) for TDOA estimation of stationary targets. First, a large number of simulation samples are generated according to the TDOA model. Each sample contains the time difference from each secondary base station to the main base station, the error of time difference, and the real three-dimensional (3-D) coordinates of the targets. Next, a suitable DNN architecture is designed to solve the solution of the stationary target position. The simulation results prove that the method proposed herein outperforms TSWLS for multiple base stations based on the TDOA model. © Published under licence by IOP Publishing Ltd.

关键词： Time difference of arrival

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Research on Question Answering System Based on BERT Model 3

Research on Question Answering System Based on BERT Model

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Yin, Jie Jiangsu University of Science and Technology School of Computer ZhenJiang China

ISBN: (纸本)9781665459112

The core of natural language processing is the science of how computers understand and respond to the influence of human language. This is also the main research direction in the field of machine intelligence development. Question answering system is one of the development directions. How to make the answer of question answering system more intelligent is the focus of research in recent years. Based on this, this thesis proposes a question answering system based on the BERT model that combines the co-attention mechanism and the self-attention mechanism. In order to better show the representation of questions and articles at their respective semantic levels, this article will choose BERT language to encode them. Attention and fusion are then performed horizontally and vertically at different levels of granularity between questions and paragraphs. Experiments show that the model has an average EM of 46.56 and an average F1 of 58.90 on all datasets. The average F1 for the development dataset is 54.85, and the average F1 for the test dataset is 62.95. The content answered by the question answering system based on the BERT model is basically reasonable, and the intelligence of the question answering system is effectively improved. © 2022 IEEE.

关键词： Semantics

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Lightweight detection method based on improved YOLOv4 3

Lightweight detection method based on improved YOLOv4

引用

3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Ruan, WenLong Liu, Yunqing Changchun University of Technology Electronic Science and Technology Changchun City China

ISBN: (纸本)9781665459112

In view of the large amount of model parameters and large amount of calculation when YOLOv4 target detection model is applied to unmanned vehicles, it is difficult to be applied to embedded platform or mobile terminal. In this paper, an improved YOLOv4 model was proposed, which used the MobileNetv1 as the backbone network of YOLOv4. The depth separable convolution was used to replace the ordinary convolution in the enhanced feature extraction network structure PANET of YOLOv4. By introducing the ECA attention mechanism and using DIOU_NMS post-processing strategy, the detection accuracy of the model was improved. The improved YOLOv4 model was tested on the PASCAL VOC data set. The results showed that the number of parameters was one-fifth of the original, the model size was reduced by 193M, the mAP was reduced by 0.56%, and the fps was increased by 20.4. It can meet the requirements of real-time detection of unmanned vehicles. © 2022 IEEE.

关键词： Object detection

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Analysis and Comparison of Various Contrast Enhancement Techniques 3

Analysis and Comparison of Various Contrast Enhancement Tech...

引用

3rd international conference on Computing, Analytics and Networks, ICAN 2022

作者： Singh, Jagdeep Kaur, Navjot Singh, Rakesh Punjabi University Department of Computer Science and Engineering Patiala India

ISBN: (纸本)9781665499446

Contrast enhancement assumes an important part in image processing which makes an image more clear and bright. It essentially improves the image quality which makes the image's content easy to recognize. In this paper the analysis of four popular contrast enhancement techniques have been done to overcome the brightness and preservation issues and also keeps up the quality of the image. These four techniques are Histogram Equalization (HE), Brightness Preserving Bi- Histogram Equalization (BBHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and Recursive Mean-Separate Histogram Equalization (RMSHE). Additionally the work also shows the estimation of various parameters like: signal to noise ratio (SNR), Mean square error (MSE), Root mean square error (RMSE), Mean absolute error (MAE), Peak signal to noise ratio (PSNR), and Structure similarity index (SSIM) for each technique. © 2022 IEEE.

关键词： Luminance

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An Efficient Feature Extraction Technique and Novel Normalization Method to Improve EMG signal Classification 3

An Efficient Feature Extraction Technique and Novel Normaliz...

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3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Jain, Reema Garg, Vijay Kumar Lovely Professional University Department of Computer Application Punjab Phagwara India Lovely Professional University Department of Computer Science & Engineering Punjab Phagwara India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

Electromyography (EMG) is one of the medical diagnostic techniques that is widely used to investigate muscular health status. Medical and paramedical professional's record EMG signals as myoelectric signals that need some processing to improve their apt analysis and interpretation. In the present paper, the authors have integrated feature extraction and normalization step to improve the overall EMG signal classification. The process involves 12 feature extraction matrices that are used for the normalization of the recorded signals. The processed signals are fed to a binary classifier, Support Vector Machine (SVM) for categorization into pain and normal classes. Performance analysis is performed using 100 simulation rounds and the observations are summarized in terms of precision, sensitivity, specificity, and accuracy of classification of EMG signals. The simulation analysis demonstrated that with the integration of feature extraction and normalization step, an improvement of 3% is observed in the EMG signal classification accuracy. © 2022 IEEE.

关键词： Support vector machines

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Bangla Language processing: Sandhi 3

Bangla Language Processing: Sandhi

引用

3rd IEEE India Council international Subsections conference, INDISCON 2022

作者： Ghosh, Samarjit Mukherjee, Souvik Roy, Debojyoti Sarkar, Sumit Sarkar, Debranjan Heritage Institute of Technology Department of Computer Science and Engineering Kolkata India

Algorithms for Sandhi Yoga (joining) and Vichchheda (Splitting) for Bangla language processing have been proposed. These algorithms may be extended to other Indian languages, including Sanskrit. These may also find wi... 详细信息

ISBN: (数字)9781665466011

ISBN: (纸本)9781665466011

关键词： Joining

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Hyperspectral Image Denoising Based on Multi-Resolution Gated Network with Wavelet Transform 3

Hyperspectral Image Denoising Based on Multi-Resolution Gate...

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Li, Kengpeng Zhong, Fenfa Sun, Lei Sun Yat-sen University School of Systems Science and Engineering Guangzhou China

ISBN: (纸本)9781665459112

Hyperspectral image denoising is an essential pre-processing task. In this paper, a multi-resolution gated network based on wavelet transform (WMRGNet) is proposed for removing mixed noise of hyperspectral images. Firstly, based on the fact that hyperspectral images have strong spectral correlation, a spatial-spectral information extraction module is designed to use the current noisy band and its adjacent bands as the input of WMRGNet. Secondly, aim to fully consider the spatial local and global information of hyperspectral images, a multi-resolution feature extraction module is proposed, applying the discrete wavelet transform to divide the resolution into four scales, and the residual blocks to extract information of different resolutions. In addition, a gated layer is introduced for cross-resolution information interaction to enhance the feature fusion. Finally, a high-resolution image reconstruction module with multiple residual blocks is employed to extract high-resolution features. In the simulated data set experiments, WMRGNet removes Gaussian, stripe and deadline noise and preserves the detailed information of the hyperspectral images. © 2022 IEEE.

关键词： Image denoising

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Optimization challenge in decision supporting systems: An overview 3

Optimization challenge in decision supporting systems: An ov...

引用

3rd IEEE international conference on Electronics, Control, Optimization and computer science, ICECOCS 2022

作者： Ridani, Mohamed Amnai, Mohamed Faculty of Science Kenitra Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

The manipulation of hypercubes (cubes) of data is a frequently used operation in the design of multidimensional data warehouses, due to their better adaptation to OLAP (On-Line Analytical processing) process. However, the update of these hypercubes is a very complicated process due mainly to the mass and the complexity of the data presented. The aims of this work are to describe in first case the state of the art of the research works dealing with optimization of enabled views to be materialized which formed the cubes named in the literature as materialized view selection problem. In the second case we described the various approaches dealing with updating process of data cube in decision support systems. © 2022 IEEE.

关键词： Data warehouses

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Distant Blurred Pedestrian Detection: Based on SSD Network with SRGAN Image Super Resolution 3

Distant Blurred Pedestrian Detection: Based on SSD Network w...

引用

3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Zhang, Naifeng Beijing Institute of Technology School of Computer Science Beijing China

ISBN: (纸本)9781665459112

Traditional target detection methods have poor accuracy when processing lower resolution images with many pedestrians, particularly for small and blurry targets whose features are not manifested as significantly as the larger, clearer ones. This paper proposes an SSD pedestrian detection method with super-resolution image enhancement to address this problem. Because the small blurry pedestrians in the distance usually appear in the central part of the image, the model this paper proposed crops the central part of the screen and enhances it using SRGAN. After that, this paper use SSD to detect the enhanced image again. The detection results are fused with the normal detection results to obtain higher pedestrian detection accuracy. For the experiments, the AP of the proposed method reaches 0.693, and F1 comes to 0.709 in the street scene, which is 0.031 and 0.061 higher than the original SSD network. Meanwhile, the AP reaches 0.722 and F1 reaches 0.737 in the denser pedestrian scene, which is 0.044 and 0.085 more elevated than the original SSD network, reflecting the significant improvements in our proposed method's detection accuracy. © 2022 IEEE.

关键词： Image enhancement

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Image Radiation Compensation Method Based on Two-dimensional Attention Module 3

Image Radiation Compensation Method Based on Two-dimensional...

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3rd international conference on computer Vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Zhang, Tianyu Zhang, Chao Han, Cheng Yang, Yihan Changchun University of Science and Technology College of Computer Science and Technology Changchun China

ISBN: (纸本)9781665459112

With the diversification of projection scene requirements and the continuous development of projection technology, various scenes containing color textures are used as projection surfaces in daily life. These projection surfaces lead to color distortion of projection image affected by color texture and affect projection effect. The radiation compensation of the projector is to counteract the impact of the textured surface on the projected image by processing the input image of the projector. Aiming at this problem, this paper proposes a color compensation network model for projected images based on a two-dimensional attention module. The model uses a convolutional neural network to learn a complex mapping between the projector input image and the image captured by the camera. An attention module is added to the feature extraction network to generate attention map refinement adaptive features. Finally, a combination of loss functions is set for the specific task of color compensation for network optimization. The experimental results show that the method proposed in this paper effectively solves the problem of color distortion of projected images caused by colored textured surfaces and improves the quality of the projection. © 2022 IEEE.

关键词： Textures

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