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检索条件"任意字段=Conference on Visual Information Processing and Communication"

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Vehicle Detection Algorithm for Foggy Roads at Night Based on Improved Gated Context Attention Network 5

Vehicle Detection Algorithm for Foggy Roads at Night Based o...

引用

5th Asia-Pacific conference on Image processing, Electronics and Computers, IPEC 2024

作者： Zhang, Liyan Zhao, Jianing Fang, Liu Lang, Zhengang School of Computer and Communication Engineering Dalian Jiaotong University Dalian China

ISBN: (纸本)9781643685243

The dim lighting at night increases the possibility of vehicle detection omissions and objects on foggy roads at night. To improve the accuracy of vehicle detection in foggy nighttime environments and strengthen road safety monitoring, this paper proposes an improved GCA Net algorithm for vehicle detection in foggy nighttime environments. Firstly, this article introduces the SE attention module after the convolutional block of GCA Net, which focuses more on the channels related to the defogging task to capture more critical information and improve the accuracy of vehicle detection. Secondly, this article adopts the MS-SSIM+L1 mixed loss function to further improve the model's attention to brightness, thereby better handling situations with darker nighttime lighting. Compared with the original GCA Net, the improved algorithm achieves a peak signal-to-noise ratio increase of 1.063dB. Once again, in order to further enhance the information content and visual effect of nighttime images, ACE nighttime image color correction and GCA Net fusion network were introduced for nighttime image dehazing to highlight the contours and details of targets such as vehicles and roads. Finally, YOLOv7 was used for vehicle target detection and experimentally validated on a real foggy dataset. The experimental results show that compared with the previous method, this method has better recognition performance in vehicle detection and recognition on foggy roads at night, successfully improving the accuracy and reliability of vehicle detection. © 2024 The Authors.

关键词： Lighting

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Accuracy of Natural Language processing Algorithms in Representing Stressed Words in Closed Captioning 27

Accuracy of Natural Language Processing Algorithms in Repres...

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27th Asia-Pacific conference on communications (APCC) - Creating Innovative communication Technologies for Post-Pandemic Era

作者： Boonmee, Prawit Jitngernmadan, Prajaks Kubola, Kanuengnij Sinwongsuwat, Kemtong Prempraneerach, Pradya Burapha Univ Fac Informat Chon Buri Thailand Prince Songkla Univ Fac Liberal Arts Hat Yai Thailand Thammasat Univ Fac Engn Bangkok Thailand

ISBN: (数字)9781665499279

ISBN: (纸本)9781665499279

For English as a Foreign Language (EFL) learners whose native tongue is not a stress-timed language, it is a difficult task to master word stress in speaking. Despite technological advances and years of learning English in school, many Thai EFL learners, in particular, are struggling with correct stress placement in English words, especially when conversing in English. With knowledge of natural language processing and English linguistics, this study creates closed captions to provide additional visual information on stress placement to help these learners making themselves better understood in English conversation. This also helps those who are deaf or hard of hearing to recognize highlighted audio narratives properly. The purpose of this study is to determine the accuracy of word stress representation in closed captions via human auditory analysis and perception. The results show that the current approach delivers 74.19% of representation accuracy.

关键词： natural language processing closed captioning algorithms English as a foreign language conversation analysis (CA)

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Some Evaluations on Spectrogram Art communications Exchanging Secret visual Messages 22

Some Evaluations on Spectrogram Art Communications Exchangin...

引用

6th International conference on Digital Signal processing, ICDSP 2022

作者： Aoki, Naofumi Ikeda, Kenichi Yasuda, Hiroshi Shen, Ying Hou, Jin Graduate School of Information Science and Technology Hokkaido University Japan Smart Solution Technology Inc. Japan Southwest Jiaotong University China

ISBN: (纸本)9781450395809

This study investigates the possibility of visual communications using spectrogram arts drawn on sound signals. This approach attempts to increase the readability of the communications so that their messages are directly understandable by human users without any advanced decoders. This paper describes some pilot studies of our spectrogram art communication system that exchanges text messages in some chatting services. The experimental results indicate that the proposed technique may have certain appropriateness. It may be employed as a sort of steganography techniques enabling sub-channel communications in a covert manner. © 2022 ACM.

关键词： Steganography

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Digital Twin Simulation System for Computer Room Equipment 6th

Digital Twin Simulation System for Computer Room Equipment

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6th International conference on Innovative Computing, IC 2023

作者： Li, Lei Zhou, Zheng Liao, Rongtao Ye, Yuxuan Hu, Huanjun Information and Communication Branch of State Grid Hubei Electric Power Company Hubei Wuhan430000 China

ISBN: (纸本)9789819920914

This paper mainly studies a digital contracture analog device and a digital contracture analog system. The device is divided into driver installation, and the first expansion installation, the second expansion installation and the third expansion installation connected with the driver installation respectively;The driver is installed to connect the upper computer and the production device;The first expansion installation, the second expansion installation and the third expansion installation are used to connect the production devices;The driver installation is used to receive the message collection command of the upper computer, collect the relevant parameters of the production device according to the message collection command, and/or remotely control and drive the first expansion installation, the second expansion installation and the third expansion installation to collect the relevant parameters of the production device, and transmit the relevant parameters to the upper computer, and use the relevant parameters to conduct system simulation of the production device. The above devices can collect a large number of relevant parameters of production equipment, and conduct simulation modeling according to relevant technical parameters through digital contracture technology. The characteristics of production equipment can also be mastered through simulation results, and its information processing speed is fast. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Digital devices

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Research and Application of visual Engineering Project Management and Control System Based on Multimodal information

Research and Application of Visual Engineering Project Manag...

引用

International conference on Computational Intelligence and communication Networks (CICN)

作者： Feng Wang Ji Wang Hao Cai Gang Yang National Energy Group Northeast Electric Power Co. Ltd. Jilin Thermal Power Plant Jilin China

ISBN: (数字)9798331505264

ISBN: (纸本)9798331505271

With the increasing scale and complexity of engineering projects, traditional project management methods are facing many challenges. The rapid development of multimodal information technology provides a new perspective and tool for project management and control. This paper proposes a visual management and control framework based on multimodal information, which mainly includes data acquisition layer, data processing layer, data analysis layer, visual display layer and feedback adjustment layer. The framework aims to achieve all-round monitoring of project progress, quality and cost by integrating various information sources. On the basis of this framework, a set of visual engineering project management and control system based on multimodal information is designed and applied to intelligent transportation, and its potential in improving traffic management efficiency and decision support ability is analyzed. Through the analysis of a case, the effectiveness of this method is verified.

关键词： visualization Social networking (online) Soft sensors Project management Transportation Control systems Video surveillance Real-time systems Stakeholders Monitoring

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Skin Cancer Classifier: Performance Enhancement Using Deep Learning Models

Skin Cancer Classifier: Performance Enhancement Using Deep L...

引用

International conference on Signal processing and communication (ICSC)

作者： Swati Mishra Megha Agarwal Department of Electronics and Communication Engineering Jaypee Institute of Information Technology Noida India

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

Skin cancer ranks among the most prevalent human malignancies, primarily diagnosed through visual methods, commencing with clinical screening, followed by dermoscopic analysis. The intricate alterations in the visual appearance of skin lesions pose a considerable challenge for automated classification through images. Deep learning techniques have been harnessed to support dermatologists in enhancing diagnostic accuracy. To address this, deep convolutional neural networks (CNNs) are employed to achieve highly discriminating and potentially generalizable results for image classification problems. This research introduces a prediction model designed to classify skin lesions into seven categories using the HAM10000 skin cancer dataset. The MobileNetV2, Resnet50, and DenseNet121 models were used in this study. The MobileNetV2 outperforms with 99.72 % accuracy and achieves 0.88, 0.89, and 0.88 values of precision, recall, and F1 score.

关键词： Deep learning visualization Analytical models Accuracy Computational modeling Skin Real-time systems Lesions Skin cancer Residual neural networks

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Binauralmusic: A Diverse Dataset for Improving Cross-Modal Binaural Audio Generation

Binauralmusic: A Diverse Dataset for Improving Cross-Modal B...

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International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Yunqi Li Shulin Liu Haonan Cheng Long Ye School of Data Science and Intelligent Media Communication University of China Beijing China School of Information and Communication Engineering Communication University of China Beijing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China

Cross-modal binaural audio generation is an important task and has broad applications such as game sound development and auditory assistance for the visually impaired. However, existing datasets lack binaural samples with abundant visual venues. As a consequence, state-of-the-art cross-modal binaural audio generation methods have weak generalization. To support research on building robust binaural audio generation, we construct BinauralMusic dataset consisting of 5,462 performance video clips with binaural audio from 9 musical instrument categories. The performance venues involve indoor closed places such as shopping mall, hotel, bedroom, as well as outdoor open areas such as field, garden and seashore. Experiments show that the performance of the cross-modal binaural audio generation model can be significantly improved by 10.62% by using the BinauralMusic dataset as training material. Moreover, different from previous datasets, the BinauralMusic dataset can also support other audio-visual cross-modal learning tasks, including visually guided sound source localization and separation.

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Uncropped Siamese Fully Convolutional Network for visual Tracking 6

Uncropped Siamese Fully Convolutional Network for Visual Tra...

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6th International conference on Video and Image processing, ICVIP 2022

作者： Cai, Zhongwang Hu, Yongqi Yang, Zhen School of Communication and Electronics Jiangxi Science and Technology Normal University China

ISBN: (纸本)9781450397568

Considering the peculiarity of SiamCAR, which decomposes visual tracking into a Siamese subnetwork for feature extraction and a classification-regression subnetwork for bounding box prediction, we propose an empirical method to avoid cropping the high-level semantic information for further anchor-free tracking tasks. Based on the preprocessing of the training image pairs, we focus on the center region of the feature maps in the template branch, which includes the whole object while reducing background clutter. However, the position of the object in a sequence is always in constant motion. The loss of high-level features causes the large movement of the object to weaken the performance of the strategy for tracking the current object in accordance with the object location of the previous frame. Therefore, we remove the inappropriate cuts to obtain a better similarity map. Extensive experiments and comparisons show that our proposed simple but effective method achieves credible results with remarkable real-Time speed on the UAV123, LaSOT and GOT-10k benchmarks. © 2022 ACM.

关键词： Classification (of information)

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Auslan-Daily: Australian Sign Language Translation for Daily communication and News 37

Auslan-Daily: Australian Sign Language Translation for Daily...

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37th conference on Neural information processing Systems, NeurIPS 2023

作者： Shen, Xin Yuan, Shaozu Sheng, Hongwei Du, Heming Yu, Xin The University of Queensland Australia JD AI Beijing China

ISBN: (纸本)9781713899921

Sign language translation (SLT) aims to convert a continuous sign language video clip into a spoken language. Considering different geographic regions generally have their own native sign languages, it is valuable to establish corresponding SLT datasets to support related communication and research. Auslan, as a sign language specific to Australia, still lacks a dedicated large-scale dataset for SLT. To fill this gap, we curate an Australian Sign Language translation dataset, dubbed Auslan-Daily, which is collected from the Auslan educational TV series and Auslan TV programs. The former involves daily communications among multiple signers in the wild, while the latter comprises sign language videos for up-to-date news, weather forecasts, and documentaries. In particular, Auslan-Daily has two main features: (1) the topics are diverse and signed by multiple signers, and (2) the scenes in our dataset are more complex, e.g., captured in various environments, gesture interference during multi-signers' interactions and various camera positions. With a collection of more than 45 hours of high-quality Auslan video materials, we invite Auslan experts to align different fine-grained visual and language pairs, including video ↔ fingerspelling, video ↔ gloss, and video ↔ sentence. As a result, Auslan-Daily contains multi-grained annotations that can be utilized to accomplish various fundamental sign language tasks, such as signer detection, sign spotting, fingerspelling detection, isolated sign language recognition, sign language translation and alignment. Moreover, we benchmark results with state-of-the-art models for each task in Auslan-Daily. Experiments indicate that Auslan-Daily is a highly challenging SLT dataset, and we hope this dataset will contribute to the development of Auslan and the advancement of sign languages worldwide in a broader context. All datasets and benchmarks are available at Auslan-Daily. © 2023 Neural information processing systems foundation. All ri

关键词： Large datasets

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Hyperspectral Image Classification Using 3D Attention Mechanism in Collaboration with Transformer 6

Hyperspectral Image Classification Using 3D Attention Mechan...

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6th International conference on Artificial Intelligence and Pattern Recognition, AIPR 2023

作者： Wang, Yubing Zhang, Ye Duan, Kaifeng School of Communication and Information Engineering Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9798400707674

With the continuous innovation in deep learning, it has become a major direction for scholars to introduce the knowledge of deep learning into hyperspectral image classification to enhance its classification accuracy. Convolutional Neural Networks (CNN) are one of the most commonly used deep learning-based visual data processing methods, and are widely used in hyperspectral image (HSI) classification by virtue of their excellent contextual modeling capability. Since the performance of HSI classification is highly dependent on spatial and spectral information, this paper proposes a hyperspectral image classification method using 3D attention mechanism in collaboration with Transformer for hyperspectral image classification in view of the problems that the current hyperspectral image classification models with the framework of CNN have insufficient spatial spectral feature extraction and fail to excavate and represent the sequence properties of spectral features well. In this paper, we introduce a variant Transformer model based on a hybrid model of both improved 3D-CNN and 2D-CNN, combining complementary information of spatial spectrum and spectra in the form of 3D convolution and 2D convolution on CNN, and adding a variant attention mechanism module to strengthen spatial texture features, while combining grouped transfer Transformer to jump connection to enable the lower layer to better learn the upper layer features. Firstly, a variant channel attention mechanism is introduced on 3D-CNN to enhance the acquisition of spectral information of image features by 3D-CNN. Secondly, a variant spatial attention mechanism is introduced to enable 3D-CNN to better acquire the spatial information of hyperspectral images in the network, and subsequently the acquired spatial and spectral feature information is passed to 2D-CNN to enable it to better acquire local feature information. Finally, the acquired image feature information is passed to the variant Transformer model to mak

关键词： Convolutional neural networks

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