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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331-340 订阅

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Research and Improvement of Load Balancing Technology Based on SIP Server Clusters 3

Research and Improvement of Load Balancing Technology Based ...

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3rd international conference on Artificial Intelligence and computer Engineering, ICAICE 2022

作者： Liu, Jun Jiang, Shuming Yang, Guoli College of Computer Science and Technology Qilu University of Technology Jinan250000 China

ISBN: (纸本)9781510663473

In order to solve the problem of unbalanced Session Initiation Protocol (SIP) requests distribution in SIP server clusters when processing concurrent task requests, an improved dynamic load balancing optimization algorithm based on SIP transactions is proposed. Firstly, according to the characteristics of SIP protocol, SIP transactions are used as the unit to measure the load, different weights are assigned to different types of transactions, and the variability between server nodes and network performance are considered to measure the load of server nodes together with the response time. Then, the load factor values dynamically obtained are used to calculate the load ratio of the server nodes and compare it with the set threshold value, and the server node with the lowest load ratio in the normal state is selected to allocate SIP requests according to the comparison results, which allows the server nodes to have a buffering process, reduces the occurrence of throughput jitter phenomenon, and effectively avoids system overload. By using the open source testing tool SIPp to conduct experiments, the results show that the improved method can solve the load imbalance problem, which makes the SIP server cluster system allocate resources efficiently and reasonably, improves the utilization of system resources, has a better balance and reliability compared with other algorithm models, and achieves the expected results. © 2023 SPIE.

关键词： Internet protocols

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Feature Selection for Nepali Part-of-Speech Tagging in a Conditional Random Fields-Based System 3rd

Feature Selection for Nepali Part-of-Speech Tagging in a ...

引用

The 3rd international conference on Frontiers in Computing and Systems (COMSYS 2022)

作者： Rai, Pooja Chatterji, Sanjay Department of Computer Science and Engineering Indian Institute of Information Technology Kalyani741235 India Department of Computer Science New Alipore College Kolkata700053 India

ISBN: (纸本)9789819926794

The features used for training any statistical model have an enormous impact on the model’s performance. The selection of features that contribute most to the prediction variable or output of concern is a crucial task. We used conditional random fields (CRF) to conduct experiments on the best feature set selection for part-of-speech (POS) tagging of Nepali text. Nepali is a resource-poor language, and its processing is still in its infancy. In this work, we have studied the effect of using various features (non-linguistic affixes, word length coupled with contextual information, along with digit and symbol checking) for improving the tagger’s performance without using any external sources like the gazetteer list, morphological rules, etc. A thorough error analysis has been carried out, followed by the manual correction of the wrongly annotated words in the training data. The proposed CRF-based POS tagger’s efficacy has been validated with 95 % accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Random processes

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Identifying, Evaluating, and Addressing Nondeterminism in Mask R-CNNs 3rd

Identifying, Evaluating, and Addressing Nondeterminism in ...

引用

3rd international conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022

作者： Price, Stephen Neamtu, Rodica Computer Science Department Worcester Polytechnic Institute WorcesterMA United States

ISBN: (纸本)9783031090363

Convolutional Neural Networks, and many other machine learning algorithms, use Graphical processing Units (GPUs) instead of Central processing Units (CPUs) to improve the training time of very large modeling computations. This work evaluates the impact of the model structure and GPU on nondeterminism and identifies its exact causes. The ability to replicate results is quintessential to research, thus nondeterminism must be either removed or significantly reduced. Simple methods are provided so that researchers can: (1) measure the impact of nondeterminism, (2) achieve determinable results by eliminating randomness embedded in the model structure and performing computations on a CPU, or (3) reduce the amount of variation between model performances while training on a GPU. © 2022, Springer Nature Switzerland AG.

关键词： Graphics processing unit

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An Automated Tool to Remove Flash Light Spots using Image processing Techniques 3

An Automated Tool to Remove Flash Light Spots using Image Pr...

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3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

作者： Shrinivasacharya, Purohit Jagadamba, G. Jagadeeshaiah, Suresh Siddaganga Institute of Technlology Information Science and Engineering Tumakuru India Scania Cv Ab Stockholm Sweden

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

An image is captured using a flash list on reflecting surfaces or glass objects, and it causes a bright light on a particular spot in an image. It is because of the direct reflection of flash resulting from glassy objects and results in loss of data over the reflected part of an image. To overcome these problems, an application is developed to capture and process the images. This application can capture the images in a single click in both with flash and without flash condition. The captured images are divided into a small number of blocks and calculate Peak signal to Noise Ratio (PSNR) value for each block. Based on these PSNR values the blocks of a flash image is replaced with blocks without flash image and while replacement image intensity of an image will change to the same as the flash image. The resultant image is free from a flashlight spot and lost information. This technique is tested on different images and tabulated the corresponding values for comparing the result. The proposed method provides intuitively better results than the pixel-wise method. This application will be used in the photography to remove the reflected objects' flashlight spot. © 2022 IEEE.

关键词： Flashlights

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Residual Feature Distillation Channel Spatial Attention Network for ISP on Smartphone 17th

Residual Feature Distillation Channel Spatial Attention Netw...

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17th European conference on computer Vision, ECCV 2022

作者： Zheng, Jiesi Fan, Zhihao Wu, Xun Wu, Yaqi Zhang, Feng Zhejiang University Hangzhou310027 China University of Shanghai for Science and Technology Shanghai200093 China Tsinghua University Beijing100084 China Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9783031250620

With the increasing popularity of mobile photography, more and more attention is being paid to image signal processing(ISP) algorithms used to improve various perceptual aspects of mobile photos. For this, a learned smartphone ISP task was proposed to develop an end-to-end deep learning-based ISP pipeline that can replace classical hand-crafted ISP and imitate target RGB images captured by digital single-lens reflex camera(DSLR). However, hardware limitations of mobile phone make it essential and challenging to achieve an acceptable trade off between computational cost and performance. In this paper, a light-weighted and powerful network named residual feature distillation channel spatial attention network (RFDCSANet) is proposed for end-to-end learned smartphone ISP task. To be specific, we employ modified residual feature distillation block(RFDB) including channel spatial attention(CSA) mechanism to progressively refine distilled features and adaptively fuse channel and spatial features. Particularly, we utilize a re-parameterizable block, namely edge-oriented convolution block(ECB) as the basic module to improve performance without introducing any additional cost in the inference stage. The proposed solution ranked 3rd in Mobile AI 2022 Learned Smartphone ISP Challenge (Track 1) with 1st place PSNR score. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smartphones

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Fusion Algorithm of WiFi and IMU for Indoor Positioning 3

Fusion Algorithm of WiFi and IMU for Indoor Positioning

引用

3rd international conference on Information science, Parallel and Distributed Systems, ISPDS 2022

作者： Wang, Qianqiu Li, Junjie Luo, Xianlu Chen, Chun School of Computer Science and Engineering Neusoft Institute Guangdong Foshan China School of Electrical & Information Engineering Changsha University of Science and Technology Changsha China

ISBN: (数字)9781665487474

ISBN: (纸本)9781665487474

Due to the limitations imposed by and complexity of indoor environments, a low-cost and accurate indoor positioning system has not yet been designed. To address this issue, we constructed a fused indoor positioning algorithm based on the extended Kalman filter for WiFi and inertial measurement units (IMUs) using only a smartphone. To reduce the influence of WiFi signal fluctuation on fingerprint-based positioning, we used Gaussian process regression for denoising the data. We used our proposed improved clustering algorithm to reduce the matching amount in the positioning stage and increase the positioning accuracy. In terms of pedestrian dead reckoning (PDR) positioning, we designed a new and effective direction estimation algorithm integrating accelerometer and magnetometer, and we used an online step size estimation model to improve the accuracy of step size estimation. The experimental results showed that the average positioning error of the proposed fusion algorithm is 1.76 m, which was 55% lower than that using the WiFi network only, and 62% lower than using PDR only. Our findings showed that the fused positioning scheme based on WiFi and IMU can be used to effectively increase indoor positioning accuracy, and the proposed system is suitable for high-precision positioning scenarios. © 2022 IEEE.

关键词： Indoor positioning systems

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A comparative analysis of Convolution Neural Network models on Amazon Cloud Service 3

A comparative analysis of Convolution Neural Network models ...

引用

3rd international conference on Artificial Intelligence, Information processing and Cloud Computing, AIIPCC 2022

作者： Doukha, Rim Mahmoudi, Sidi Ahmed Zbakh, Mostapha Manneback, Pierre Computer Science Department FPMs University of Mons Mons Belgium National Higher School of Computer Sciences and Systems Analysis Mohammed V University Rabat Morocco

ISBN: (纸本)9783800759330

Deep Learning (DL) is increasingly used in Cloud Computing services, where almost unlimited computing resources are available to accelerate the training, testing, and deployment of models. However, it is important to mention the challenges that developers may face when using a Cloud services, for instance the variation of application requirements over time in terms of computation, memory and energy consumption. This variation may require migration to higher performance resources. Indeed, Cloud services dedicated to DL applications such as Graphics processing Unit (GPU) resources are quite expensive, specifically for small and medium companies. In this context, it is beneficial for Cloud users to understand the needs of DL applications in order to guarantee the well-functioning of their applications over time and reduce the cost of the allocated resources. While considering the importance and the complexity of Convolutional Neural Networks (CNN) in DL, this paper presents a comparative analysis of different types of CNN models (ResNet50, VGG16, VGG19, Inception-v3, Xception) in order to find out when migrating to more powerful GPUs is advantageous in terms of execution time and cost. This analysis was conducted by extracting GPU usage, execution time and associated costs for training models and was performed using Amazon Elastic Computing (EC2) instances dedicated to DL and Amazon CloudWatch for monitoring model metrics. Experimental results showed that is recommended to migrate models using more than 90% of GPU performance to more powerful infrastructures compared to those using less than 90%. © VDE VERLAG GMBH.

关键词： Graphics processing unit

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Study on Improved YOLOv7-based Algorithm for Detecting Crack Defects in Ancient Buildings 24

Study on Improved YOLOv7-based Algorithm for Detecting Crack...

引用

3rd international conference on computer, Artificial Intelligence and Control Engineering, CAICE 2024

作者： Fang, Tianke Hui, Zhenxing Rey, William P Xie, Zhiying Yang, Aihua He, Yuanrong School of Information Technology Mapua University Manila1200 Philippines Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen Fujian361024 China School of Computing and Information Engineering Xiamen University of Technology Xiamen Fujian361024 China School of Information Media Zhangzhou Vocational College of Science and Technology Zhangzhou Fujian363200 China Hunan Key Laboratory of Remote Sensing Monitoring of Ecological Environment Dongting Lake Area Changsha Hunan410004 China

ISBN: (纸本)9798400716942

In the protection and restoration work of ancient buildings, the detection and analysis of the cracks and defects of the exterior walls of ancient buildings is a crucial task. In this paper, an improved YOLOv7 algorithm is proposed to detect the defects of ancient external walls, aiming to achieve efficient and accurate detection of the defects of ancient external walls. The method involves preprocessing the image using a rectangle clipping algorithm, graying the image using the maximum method, and denoising the image with a median filter. Next, the image is labeled using the LabelImg tool, and the data is split into training, validation, and test sets. During model training, a CBAM-Net module is inserted after several CBS modules in the backbone network, the GIOU loss function is replaced by CIOU, and feature task extraction is performed. The realized attention mechanism is added to the Yolov7 model. The results show that the mAP value of crack detection after the improved algorithm reaches 81.2%. In contrast to the initial YOLOv7 algorithm, the precision of the model has been boosted to 87.2%, exhibiting a 6.0% enhancement in accuracy and an 85.2% improvement in recall rate. The improved YOLOv7 crack detection algorithm reduces network calculation and improves crack classification and recognition ability. This approach is crucial in safeguarding ancient buildings as it enables varying levels of maintenance depending on the severity of cracks. © 2024 ACM.

关键词： Attention mechanism Deep learning Defect detection Image processing YOLOv7

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An Experiment on Speech-to-Speech Translation of Hindi to English: A Deep Learning Approach 3rd

An Experiment on Speech-to-Speech Translation of Hindi to ...

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3rd international conference on Machine Intelligence and signal processing, MISP 2021

作者： Singh, Sakshi Singh, Thoudam Doren Bandyopadhyay, Sivaji Department of Computer Science and Engineering National Institute of Technology Silchar Silchar India

ISBN: (纸本)9789811908392

The purpose of this paper is to design and develop a complete Hindi-to-English speech-to-speech translation system. We employ three modules, i.e. automatic speech recognition (ASR), neural machine translation (NMT) and text-to-speech (TTS). The ASR recognizes speech signal in source language A (i.e. Hindi) and gives the text version of it. The NMT converts the source language’s text into the target language’s text. The TTS module converts the text of the target language into speech (i.e. English). We carry out the experiment of the end-to-end architecture despite the complexity of the speech translation system with reasonable performance. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Speech synthesis

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Rating Meter for Digital Terrestrial Television with ISDB-T Standard Through Transport Stream Analysis 1

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3rd international conference on Applied Technologies, ICAT 2021

作者： Olmedo, Gonzalo Malusin, Erick Paredes, Nancy WiCOM-Energy Research Group Department of Electrical Electronics and Telecommunications Universidad de Las Fuerzas Armadas ESPE Sangolquí Ecuador Engineering in Electronics and Telecommunications Universidad de Las Fuerzas Armadas ESPE Sangolquí Ecuador

ISBN: (数字)9783031038846

ISBN: (纸本)9783031038839

The television programming rating represents, as a percentage, the number of households or viewers who find the television turned on a given channel, program, day, and time. In this project, a rating meter was implemented for the international ISDB-T system based on the analysis of the Program Specific Information tables and Service Information tables of the Transport Stream that carries the information of the television channels and the content of the Electronic Programming Guide, whose data is recorded in a database implemented for this purpose, where the viewer does not need to interact or answer questions about the programming. The implemented prototype uses a full-seg ISDB-T receiver to capture the signal from the air and obtain the transport flow. For the information processing, an interface was designed in Java that evaluates the flow based on the service tables, event information, time offset, and the descriptors that describe information about each event. The data with the name of the channel, name of the program, type of service, start and end time are recorded in the database and automatically generate the rating report. The tests were carried out with the reception of open television channels in the city of Quito in Ecuador. © 2022, Springer Nature Switzerland AG.

关键词： signal receivers

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