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Deep Learning Fusion Ensemble for Enhanced Traffic Sign Detection Using the ICTS Dataset

Deep Learning Fusion Ensemble for Enhanced Traffic Sign Dete...

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International conference on Applied Electromagnetics, signal processing and Communication (AESPC)

作者： Samir Kumar Majhi Rahul Kumar Gupta Binayak Ojha Aaron Sapkota Debendra Muduli Department of Computer Science C.V. Raman Global University Bhubaneswar India

ISBN: (数字)9798331528171

ISBN: (纸本)9798331528188

Traffic Sign Identification and Detection(TSID) sys- tems are vital components of advanced and smart driving systems as well as autonomous vehicles. Our proposed model, based on deep learning, specifically trains and evaluates convolutional neural networks (CNN) using ensemble pre-trained models such as VGG16 and ResNet50 from the field of transfer learning for image classification and combines them in a fusion ensemble model. We leveraged data augmentation strategies to increase the training images during preprocessing. Our data and outcomes show that the fusion of the proposed model performed better, achieving a classification accuracy of 99.70 % using the ICTS (Indian Cautionary Traffic Sign) dataset compared to some traditional models.

关键词： Deep learning Training Adaptation models Accuracy Transfer learning Data models Road safety Convolutional neural networks Residual neural networks image classification

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Communication Base Station Traffic Prediction Based on Nonlinear Regression-LSTM Decomposition Algorithm

Communication Base Station Traffic Prediction Based on Nonli...

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signal processing, Communications and Engineering Management conference (ISPCEM), International

作者： Yanhe Tao >School of Marine Science and Technology Northwestern Polytechnical University Xi’an China

ISBN: (数字)9798331528676

ISBN: (纸本)9798331528683

Communication base station traffic prediction can help network service providers predict the peak hours of network traffic, so as to carry out network expansion and load balancing in advance, and keep the users getting a smooth network experience even during the peak hours of the network. In order to accurately predict traffic usage in different time periods, we first constructed a nonlinear regression model, then solved the parameters in the algorithm, and finally got the image of our predicted nonlinear function and compared it with the real value, and found that there are some small swings. Finally, we use the LSTM recurrent neural network to predict the swing term. the final flow prediction is obtained which is very close to the real situation. the model performance was verified with MAE, MAPE and RMSE metrics respectively, and the results showed that the values of the three metrics were 0.1873, 0.0978 and 0.2260 respectively.

关键词： Measurement Analytical models Base stations Recurrent neural networks Time series analysis signal processing algorithms Telecommunication traffic Predictive models Prediction algorithms Long short term memory

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Multichannel Computer Screen Recording System Based on FPGA and ARM

Multichannel Computer Screen Recording System Based on FPGA ...

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2011 4th IEEE International conference on Computer Science and Information Technology(ICCSIT 2011)

作者： Chun-Feng Liang Electronic Engineering Department Tsinghua University Beijing,China Yan-Fa Tang Institute of Microelectronics Tsinghua University Beijing,China Bing-Chan Li Electronic Engineering Department Tsinghua University Beijing,China Hong-Liang Sun Institute of Microelectronics Tsinghua University Beijing,China

A multichannel computer screen recording system based on Field Programmable Gate Array (FPGA) and Advanced RISC Machines (ARM) is introduced in this *** system has both Video Graphics Array (VGA) and Digital Video Interface (DVI) inputs,and supports the resolution of 1920x1080 and any common resolutions that do not exceed *** system can simultaneously record VGA and DVI signal by using the FPGA as the MUX of VGA and *** experimental results showed that the algorithm used in this system,which combined the wavelet transform and listless zerotree entropy coding,achieved significantly higher quality of the decoded images than JPEG with the same compression *** mapping of FPGA to SRAM method ensures the bit stream band width between FPGA and *** the compression ratio of 50,the system can record 20 frames per second at the resolution of 1600x1200.

关键词： Screen record image compression FPGA implementation wavelet transform 1600x1200

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TCIE-ResNeXtGAN: infrared and water vapor satellite image fusion model using dual discriminator generative adversarial networks and ResNeXt for improving tropical cyclone intensity estimation accuracy

TCIE-ResNeXtGAN: infrared and water vapor satellite image fu...

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2022 conference on Infrared, Millimeter, Terahertz Waves and applications, IMT 2022

作者： Guo, Jia-Xu Zhang, Chang-Jiang College of Physics and Electronic Information Engineering Zhejiang Normal University Jinhua321004 China Taizhou University Taizhou318000 China

ISBN: (纸本)9781510662476

Different characteristics of satellite images are reflected in different channels, so the monitoring and early warning of meteorological disasters based on satellite image data of a single channel may not achieve satisfactory results. the infrared channel satellite image reflects the ground and cloud top infrared radiation or the temperature distribution. the water vapor channel satellite image reflects the spatial distribution of water vapor in the upper atmosphere. the two channel satellite images reflect atmospheric characteristics from different wavebands. this paper proposes an infrared and water vapor channel satellite image fusion model (TCIE-ResNeXtGAN) based on dual discriminator generative adversarial network and ResNeXt to improve the accuracy of tropical cyclone (Tropical Cyclone, TC) intensity estimation. For this reason, we define the factors affecting TC intensity estimation, namely the brightness temperature gradient in satellite images, based on our previous work, and introduce it to the loss function in the proposed deep learning model to guide the training process of the model. In this way, the purpose of improving the estimation accuracy of TC intensity using fused satellite images is achieved. To demonstrate the effectiveness of the fusion results in this paper, we compare performance between the existing three models and our model. the experimental results show that the proposed image fusion method in this paper can preserve the infrared and water vapor dual-channel information to the greatest extent, while improving the estimation accuracy of TC intensity using fused satellite image. © 2023 SPIE.

关键词： Generative adversarial networks

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A computational model of neural contour processing: Figure-ground segregation and illusory contours

A computational model of neural contour processing: Figure-g...

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International conference on Computer Vision (ICCV)

作者： F. Heitger R. von der Heydt Communication Technology Laboratory Swiss Federal Institute of Technology Zurich Switzerland Department of Neurology University Hospital Zurich Zurich Switzerland

the detection of occluding contours in images of 3-D scenes is a fundamental problem of vision. the authors present a computational model of contour processing that was suggested by neurophysiological recordings from the monkey visual cortex. the model uses convolutions and nonlinear operations, but no feedback loops. Contours are defined by the local maxima of the responses of a contour operator that sums a representation of contrast borders and a grouping signal. the grouping consists of convolving a representation of key-points, such as T-junctions, corners, and line ends, with a set of orientation selective kernels, and a nonlinear pairing operation. the grouping scheme is selective based on whether the configuration of key-points is consistent with the interpretation of occlusion. the resulting contour representation includes an indicator of figure-ground direction. It is shown that the model reproduces illusory contours in accurate agreement with perception and generates representations of occluding contours on images of natural scenes that are more complete and less cluttered by spurious connections of foreground and background than those obtained by conventional edge detection operators.< >

关键词： Computational modeling Layout Brain modeling Feedback loop image edge detection Communications technology Laboratories Nervous system Hospitals Kernel

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Human-posture classification for intelligent visual surveillance systems - art. no. 69830F

Human-posture classification for intelligent visual surveill...

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conference on Defense and Security - Special Sessions on Food Safety, Visual Analytics, Resource Restricted Embedded and Sensor Networks, and 3D Imaging and Display

作者： Rababaah, Haroun Shirkhodaie, Amir Tennessee State Univ Dept Mech & Mfg Engn Ctr Excellence Battlefield Sensor Fus Nashville TN 37209 USA

ISBN: (纸本)9780819471819

Intelligent surveillance systems (ISS) have gained a significant attention in recent years due to the nationwide security concerns. Some of the important applications of ISS include: homeland security, border monitoring, battlefield intelligence, and sensitive facility monitoring. the essential requirements of an ISS include: (1) multi-modality multi-sensor data and information fusion, (2) communication networking, (3) distributed data/information processing,, (4) Automatic target recognition and tracking, (5) Scenario profiling from discrete correlated/uncorrelated events, (6) Context-based situation reasoning, and (7) Collaborative resource sharing and decision support systems. In this paper we have addressed the problem of human-posture classification in crowded urban terrain environments. Certain range of human postures can be attributed to different suspicious acts of intruders in a constrained environment. By proper time analysis of human trespassers' postures in an environment, it would be possible to identify and differentiate malicious intention of the trespassers from other normal human behaviors. Specifically in this paper, we have proposed an image processing-based approach for characterization of five different human postures including: standing, bending, crawling, carrying a heavy object, and holding a long object. Two approaches were introduced to address the problem: template-matching and Hamming Adaptive Neural Network (HANN) classifiers. the former approach performs human posture characterization via binary-profile projection and applies a correlation-based method for classification of human postures. the latter approach is based a HANN technique. For training of the neural, the posture-patterns are initially compressed, thresholded, and serialized. the binary posture-pattern arrays were then used for training of the HANN. the comparative performance evaluation of both approaches the same set of training and testing examples were used to measure th

关键词： intelligent surveillance human-posture classification signal-processing-based binary-profile characterization correlation-based template-matching Hamming neural networks

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Approximate Logic Synthesis and its Application in image signal Processor 16

Approximate Logic Synthesis and its Application in Image Sig...

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16th IEEE International conference on Solid-State and Integrated Circuit Technology, ICSICT 2022

作者： Li, Yukun Li, Zhen Wang, Yifan Zhang, Wenbo Xiong, Botao Ma, Yanhua Shen, Rensheng Li, Zhaohan Liu, Guowen Chang, Yuchun Dalian University of Technology School of Microelectronics Dalian116024 China Beijing Institute of Aerospace Control Devices China

ISBN: (数字)9781665469067

ISBN: (纸本)9781665469067

As power consumption in digital systems grows rapidly, energy efficiency has become a crucial concern. To address this, approximate computing was proposed as an innovative paradigm. In this work, we realize an approximate logic synthesis (ALS) toolchain utilizing Boolean matrix factorization algorithm based on error sharping technique (ESBMF) and open-source tools, its basic operation is to generate the corresponding approximation circuit by different input error thresholds. Moreover, we also present an approximate image signal processor (APPROX-ISP). Compared to the original counterpart, APPROX-ISP achieves area benefits of 44.2%, 36.7%, 34.1%, 34.5%, power consumption benefits of 49.9%, 38.6%, 37.1%, 52.2%, and delay benefits of 57.6%, 34.9%, 51.0%, 19.5% using 12-bit Adder, 14-bit Adder, 15-bit Adder and 8-bit Multiplier, respectively. Our experiment demonstrates that there is almost no accuracy degradation in machine learning tasks while using APPROX-ISP. © 2022 IEEE.

关键词： Adders

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Hierarchical object-oriented video segmentation and representation algorithm

Hierarchical object-oriented video segmentation and represen...

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International conference on signal processing Proceedings (ICSP)

作者： Jianping Fan G. Fujita Jun Yu K. Miyanohana T. Onoye N. Ishiura Lide Wu I. Shirakawa Department of Information Systems Engineering Faculty of Engineering Osaka University Suita Osaka Japan Department of Computer Science Fudan University Shanghai China

In this paper, a novel object-oriented hierarchical video segmentation and representation algorithm is proposed based on a four-component video model, where the local variance contrast and the frame difference contrast are selected for generating the 2D spatiotemporal entropy. the extracted object is first represented by a group of (4/spl times/4) blocks coarsely, then the intra-block edge extraction on edge blocks and the joint spatiotemporal similarity test among neighboring blocks are further performed for determining meaningful real objects. this proposed hierarchical segmentation algorithm may be very useful for MPEG-4 applications. A novel fast algorithm is also introduced for reducing the search burden. Moreover, this unsupervised algorithm also makes automatic image and video segmentation possible.

关键词： image segmentation Entropy Object oriented modeling Spatiotemporal phenomena Layout Bit rate Video coding Humans Information systems Systems engineering and theory

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A Heart Sound Identification System Built on Android-Based Electronic Stethoscope for Healthcare Development

A Heart Sound Identification System Built on Android-Based E...

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International conference on Electrical Engineering, Computer Science and Informatics (EECSI)

作者： Rachmad Setiawan Nada Fitrieyatul Hikmah Shalfienna Alya Khansa Department of Biomedical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

Heart disease is a significant cause of death worldwide and the highest cause of death in Indonesia. With over 7000 islands, the geography of Indonesia presents substantial challenges in managing heart disease, particularly in remote and underdeveloped areas. Early detection is crucial in reducing mortality rates associated with heart disease. However, this process can be expensive and relies heavily on clinicians for accurate detection. Technological advancements have led to smartphones with increasingly sophisticated capabilities, supporting the development of mobile health applications for remote health monitoring. this study aims to develop an electronic stethoscope with a total hardware cost under a hundred rupiah that connects to an Android-based smartphone application for heart sound signal identification. the application provides a reliable validation method that reduces reliance on clinicians. Heart sound signal processing uses the fifth level of the Discrete wavelet Transform method for noise reduction, using Daubechies 4 as the mother wavelet and the Linear Envelope method for heart sound identification. the instrument design incorporates a cost-effective stethoscope, setting it apart from other electronic stethoscopes on the market. the heart sound identification method was tested on 20 individuals, and it was found that the recorded heart signal data generated accurate identification results in 95.67% of total heart cycles.

关键词： Heart Continuous wavelet transforms Accuracy Clothing Stethoscope Discrete wavelet transforms Object recognition Consumer electronics Smart phones Diseases

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Improving the quality of depth image based rendering for 3D Video systems

Improving the quality of depth image based rendering for 3D ...

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IEEE International conference on image processing

作者： Zefeng Ni Dong Tian Sitaram Bhagavathy Joan Llach B. S. Manjunath Department of Electrical and Computer Engineering University of California Santa Barbara USA Thomson Corporate Research Princeton NJ USA

ISBN: (纸本)9781424456536;9781424456543

In 3D video (3DV) applications, a reduced number of views plus depth maps are transmitted or stored. When there is a need to render virtual views in between the actual views, the technique of depth image based rendering (DIBR) can be used to generate the intermediate views. To address the problem of noisy depth information in 3DV systems, we propose novel methods that can be easily incorporated into DIBR to improve synthesized image quality. these include: (1) a heuristic scheme with adaptive spatting that blends multiple warped reference pixels based on their depth, warped pixel positions and camera parameters; (2) an approximation of the first scheme with up-sampling for fast processing; (3) boundary only splatting; and (4) view weighting based on hole distribution. Experiment results show that the proposed methods can improve synthesis quality significantly.

关键词： Rendering (computer graphics) Cameras signal synthesis image quality Layout Pixel Application software Interpolation three dimensional displays Glass

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