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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181-190 订阅

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Study on the difference of brain visual information processing between Parkinson's disease patients with hallucinations and healthy people based on EEG 3

Study on the difference of brain visual information processi...

引用

3rd international conference on computer science and Communication Technology, ICCSCT 2022

作者： Qu, Liangcheng Liu, Chuan Yin, Kuiyin Zhang, Li Shen, Bo Nanjing Research Institute of Electronic Techology Jiangsu Najing China Department of Geriatrics Affiliated Brain Hospital of Nanjing Medical University Jiangsu Najing China

ISBN: (纸本)9781510661240

computer vision is a mode task that uses computer to learn from training data and apply the learned experience to specific task. When patient experiences hallucinations, brain will call the memory stored in the hippocampus and process through specific pattern, and brain visual terminal will receive the image that does not exist in the real world. Patients with Parkinson's disease (PD) for more than 10 years are usually accompanied by hallucinations, which leads to changes in visual information processing and information perception pathway in brain. Electroencephalogram (EEG) is a spontaneous electrophysiological signal of the brain, which can reflect the working mechanism of the brain. In order to explore the changes of brain information perception pathway in PD, we recruited 5 PD patients with hallucinations, 5 healthy elderly and 5 healthy young subjects to participate visual classification experiment. The EEG collected in the experiment was analyzed by spectrum and brain network. The analysis found that the Delta, theta and alpha power of frontal lobe and occipital lobe in PD patients increased, the beta and gamma power decreased, and the brain fell into the internal circulation, the interaction between brain regions decreased. The lack of interaction may be one of the main causes of hallucinations. © 2022 SPIE.

关键词： Brain

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Systematic Literature Review on Application of Artificial Intelligence in Cancer Detection Using Image processing 3

Systematic Literature Review on Application of Artificial In...

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3rd international conference on Artificial Intelligence and Data sciences, AiDAS 2022

作者： Chandra, Giovanni Irisha, Kevina Diva Vica, Vivianit Indyca Suri, Puti Andam Syahputra, Muhammad Edo School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Having a low survival rate, cancer has become one of the deadliest diseases with complicated prognosis. In this matter, Artificial Intelligence (AI) is frequently used to aid humans due to the difficulties of cancer identification. Specifically, the use of AI in cancer detection and treatment uses two of its subclasses, machine learning and deep learning. Because those two subclasses can handle large amounts of data, their algorithms can support humans in making decisions that yield the best possible results with the least amount of risk. The purpose of this research is to find out the effectiveness of the Artificial Intelligence algorithm that is used in image processing to diagnose cancer and what is the most effective image processing algorithm for cancer diagnosis. The methods that are used in this research is Systematic Literature Review (SLR). As a result, Artificial Intelligence algorithms are sufficiently effective to be used in diagnosing cancer with image processing. Meanwhile, the most effective algorithm is CatBoost with AUC of 0.939 and Support Vector Machine (SVM) with AUC of 0.934. © 2022 IEEE.

关键词： Image processing

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A large convolution model with large receptive field for human pose estimation 3

A large convolution model with large receptive field for hum...

引用

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

作者： Liu, Zongyou Jin, Qinghan Liang, Hongwei Wang, Yuhan Qiu, Fengyi Liu, Shilan School of Computer Science Shenyang Aerospace University Shenyang China

ISBN: (纸本)9783800759330

We propose a large convolution model to complete the human pose estimation task, which has a large effective receptive field and reduces the destruction of channel information by the ReLU function. We adjusted the model of lightweight Openpose and used the structure of mobilenetv3 as the backbone of lightweight Openpose, hoping to use the InvertedResidual structure to reduces the destruction of channel information by the ReLU function. Insert RepLKBlock into the backbone to improve the effective receptive field of the model. Our model improves the following problems of the lightweight Openpose model. (1) Lightweight Openpose has a small effective receptive field. (2) The destruction of information by the ReLU function of lightweight Openpose. Large convolution model achieves Average Precision (AP) of 0.47 on the COCO2017 validation set. © VDE VERLAG GMBH.

关键词： Convolution

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Abstractive Text Summarization Using Hybrid Methods 3

Abstractive Text Summarization Using Hybrid Methods

引用

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

作者： Daga, Gautam Saha, Subhradeep Shah, Yash Nirmala, S Jaya National Institute of Technology Department of Computer Science and Engineering Tiruchirappalli India

ISBN: (数字)9781665410052

ISBN: (纸本)9781665410052

Text summarization involves the process of constructing a concise, condensed, short, coherent, and fluent summarized version of a comparatively longer document with more text and involves the process of collection and segregation of the text's major note points. There are broadly two different kinds of approaches that can be used for the process of text summarization - a) Extractive Summarization(selects important sentences as a subset of original text) and b) Abstractive Summarization(introduces new words to create a meaning summary). Hybrid methods try to incorporate a combination of both the above models, extractive and abstractive to summarize the text where the final summary can either be abstractive or extractive based on the relative positioning of the two models. © 2022 IEEE.

关键词： Text processing

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Research on deep learning algorithms for point cloud upsampling 3

Research on deep learning algorithms for point cloud upsampl...

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3rd international conference on Digital signal and computer Communications, DSCC 2023

作者： Li, Jin Gong, Yan Li, Jiao Yue, Rui Li, Ji Department of Computer and Information Security Guilin University of Electronic Technology China Department of Computer and Artificial Intelligence Changzhou University China Science Island Branch of Graduate School University of Science and Technology of China China School of Nanotechnology and Nanobionics University of Science and Technology of China China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

The integration of 3D vision technology has profoundly impacted various aspects of our lives, with point clouds emerging as the predominant geometric representation in the field due to their simplicity, ease of processing, and low acquisition costs. However, limitations in 3D scanning hardware often result in sparse, noisy, and unevenly distributed point clouds, which impede the effectiveness of subsequent 3D vision tasks. To obtain high-quality and precise point clouds, researchers have introduced upsampling algorithms that enhance point cloud representativeness through *** recent years, deep learning has supplanted traditional algorithms that rely on a priori data, owing to its robust learning representation capabilities and data-driven nature. Consequently, deep learning algorithms for point cloud upsampling have become a highly valuable research direction within the 3D vision domain. This paper delves into recent advancements in deep learning algorithms for point cloud upsampling by first defining the problem and analyzing the technical challenges from six perspectives. It then provides an overview of the relevant benchmarks in point cloud upsampling and traces their developmental *** paper further examines the technical issues in the three critical steps (point cloud local feature extraction, feature space expansion, and coordinate reconstruction) of the overall deep learning algorithm for point cloud upsampling. It categorizes the prevalent technical solutions, discussing their merits and drawbacks, and offers optimization strategies. Lastly, the paper presents a forward-looking perspective on potential research directions in this field from four angles. © 2023 SPIE.

关键词： Learning algorithms

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Medical Voice Question-Answering Interactive System Based on Speech Recognition Technology 3

Medical Voice Question-Answering Interactive System Based on...

引用

3rd international conference on Intelligent Computing and Human-computer Interaction, ICHCI 2022

作者： Xin, Haihui Zhang, Shanshan Dalian University of Science and Technology Dalian China Dalian Maritime University Dalian China

ISBN: (纸本)9781510661301

The traditional medical voice question and answer interactive system can not meet the core needs of patient consultation service, and the patient's satisfaction with the system answer is low, so the research of medical voice question and answer interactive system based on speech recognition technology is proposed. In the hardware of the system, the control core of the system is the MCU module, which controls the normal operation of the whole system, realizes the conversion of the analog signal and digital signal through the audio input device, designs the serial communication device to transmit the data information to the computer, and uses the speech recognition technology to realize the software part of the system. And through the system test, the medical voice question and answer interactive system based on speech recognition technology is compared with the traditional medical question and answer interactive system. The experimental results show that the average response time of the medical voice question and answer interaction system based on speech recognition technology to the user request is far less than the traditional system, there is no number of error requests, and the performance is better than the traditional system. Therefore, it can be proved that the performance of the medical question and answer interactive system based on speech recognition technology has reached the expected standard, and can meet the basic needs of users for medical consultation services. © 2023 SPIE.

关键词： computer control systems

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Lung Cancer Detection Using Convolutional Neural Network 3

Lung Cancer Detection Using Convolutional Neural Network

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3rd international conference on Issues and Challenges in Intelligent Computing Techniques, ICICT 2022

作者： Jain, Dhyanendra Singh, Prashant Pandey, Amit Kumar Singh, Mayank Singh, Harikesh Singh, Amarjeet Abes Engineering College Department of CSE-AIML Ghaziabad India Sunder Deep Engineering College Department of Computer Science and Engineering Ghaziabad India Jss Academy of Technical Education Department of Computer Science and Engineering Noida India

ISBN: (纸本)9781665482684

Automatic detection of defects and abnormalities in CT scan images has gain lot of importance in the recent times as because of the deteriorating quality of air almost everyone is facing one or the other type of lung related issues thus it is of esteem importance to study the computed tomography (CT) images of the pulmonary nodules to efficiently treat the diseases like lung cancer. The use of machine learning is an efficient way to distribute the work of doctors and process the large amount of data to produce accurate results on the go. Three phases of CT image pre-processing, Deep Learning, and Convolutional Neural Network use make up the diagnosis approach. The pre-processing converts raw data into usable form and deep learning algorithm assigns weight to the data, in the last stage CNN is use to conclude the health status of the lung, i.e. normal or abnormal. © 2022 IEEE.

关键词： Convolutional neural networks

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Multi-label topic classification for COVID-19 literature annotation: A BioBERT-based feature enhancement approach 3

Multi-label topic classification for COVID-19 literature ann...

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2022 3rd international conference on computer Information and Big Data Applications, CIBDA 2022

作者： Wang, Xin Wang, Jian Tang, Wentai Zhang, Hongtong College of Computer Science and Technology Dalian University of Technology Dalian116024 China

ISBN: (纸本)9783800758760

With the rapid expansion and exponential growth of biomedical literatures, especially in the current environment of COVID-19 pandemic, it is urgent to explore an effective technology to automatically manage and categorize massive information for biomedical texts. The wide application and powerful performance of BERT have shown promising results in the field of natural language processing. Thus, we first choose the improved pre-trained language models CovidBERT and BioBERT as the basis, from the best performance of which further enhances semantic representation of abstract with extra title information. Finally, a novel feature enhancement method is proposed to exploit and integrate the distribution of label information effectively. The experimental results show that our model achieves an instance-based F1 score, precision and recall of 93.94%, 93.5% and 94.38% in the task of multi-label topic classification from track 5 BioCreative VII. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： COVID-19

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Research on patent classification based on hierarchical label semantics 3

Research on patent classification based on hierarchical labe...

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3rd international conference on Education, Knowledge and Information Management, ICEKIM 2022

作者： Chen, Jie Zhao, Shu Lu, Fan Liu, Feng Zhang, Yangping Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing Hefei China Anhui University School of Computer Science and Technology Hefei China

ISBN: (纸本)9781665416665

Patent classification is an essential task in patent information management and knowledge mining. Most existing studies are based on the textual content of individual patent texts (e.g., titles and abstracts) for classification, but the patent also has label information with hierarchical structure and semantic description. However, the semantics correlation of patent texts and their labels have been largely ignored. In this paper, we propose a novel framework called HLSPC for patent classification by leveraging the hierarchical semantics correlation of patent texts and their labels. Specifically, we first apply a patent representation learning module for capturing the semantics representation of patent texts and hierarchical labels. Then, we design a label attention learning module to build the semantics correlation between patent texts and hierarchical labels, which enhances patent representation. Finally, we deploy a multi-level fusion module to get the refined category prediction for each patent which can preserve both local and global hierarchical prediction information. Extensive experimental results on two English patent datasets demonstrate the effective power of the HLSPC model. © 2022 IEEE.

关键词： Semantics

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Maximum flattened fractional delay filter based on farrow structure 3

Maximum flattened fractional delay filter based on farrow st...

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3rd international conference on Advanced Algorithms and signal Image processing, AASIP 2023

作者： Du, Shuang Song, Yaoliang Jin, Congwei Zhu, Yuting School of Electronic and Optical Engineering Nanjing University of Science and Technology 200 Xiaolingwei Street Nanjing China

ISBN: (纸本)9781510668522

The fractional delay filters are widely used in beamforming of broadband signals;however, conventional digital fractional delay filters are associated with high computational complexity. The Farrow structure fractional delay filter features a multi-stage sub-filter parallel structure, where the fractional delay is not affected by the sub-filter coefficients, thereby minimizing computational complexity. Nevertheless, the conventional Farrow structure is plagued by considerable passband fluctuations and high-frequency errors. To tackle these concerns, this article proposes a Farrow structure fractional delay filter design approach based on the maximum flatness method. This technique employs the maximum flatness method to design Farrow structure sub-filters, thereby reducing high-frequency errors and passband fluctuations compared to the conventional Farrow structure. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Computational complexity

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