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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

共 4197 条记录，以下是511-520 订阅

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Deep Learning Based Jujube Quality Assessment: An Automated Surface Defect Detection Approach 24

Deep Learning Based Jujube Quality Assessment: An Automated ...

引用

7th international conference on Signal processing and Machine Learning, SPML 2024

作者： Gao, Yujie Yuan, Baoxi Zhu, Qing Zhao, Jiyuan Ma, Xiangyang Chen, Jialu Wang, Feng Chu, Peng Wang, Chunlan School of Electronic Information Xijing University China Beijing Hengyue Intelligent Information Technology Co. Ltd. China School of Computer Science Xijing University China Graduate Office Xijing University China

ISBN: (纸本)9798400717192

Defects such as bird pecking, splitting, and mildew can affect the quality of red jujubes during their growth, transportation, and processing. To ensure the quality of red jujube products, grading the appearance of the jujubes is particularly important. Utilizing computer vision technology for classifying the appearance of red jujubes is a more cost-effective, faster, and more accurate alternative to manual screening. this paper introduces a method for grading the appearance of red jujubes based on YOLOv8. the results include a detection model with an mAP50 of 0.987 and a segmentation model with an mAP50 of 0.986, both based on the YOLOv8s model and a segmentation model with an mAP50 of 0.985 based on the YOLOv8n model. By employing the advanced YOLOv8 algorithm for jujube Surface Defect Detection, this study holds significant implications for improving quality control in the jujube industry. this technology not only enhances detection efficiency but also reduces labor costs, aligning with the trend toward industrial automation and intelligence. It offers scientific support to jujube enterprises, boosts their competitiveness, and contributes to elevating the development of agriculture to a higher standard. © 2024 ACM.

关键词： Wages

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Implementing Machine Learning Algorithms to Indentify Distributed Denial-of-Service Attacks 7

Implementing Machine Learning Algorithms to Indentify Distri...

引用

7th international conference on Image information processing, ICIIP 2023

作者： Mehra, Ankush Singh, Gurpreet Badotra, Sumit Kaur, Balwinder Verma, Amit Lovely Professional University Department of Computer Science And Engineering Punjab Phagwara India Bennett University School of Computer Science Engineering And Technology Greater Noida India University Center For Research And Development Chandigarh University Department of Computer Science And Engineering Mohali Gharuan India

ISBN: (纸本)9798350371406

An Internet server, service, or network may be the subject of a distributed denial-of-service (DDoS) assault, in which the attacker attempts to interrupt regular traffic by flooding the target with an excessive amount of data requests. Network security has been severely compromised as a result. We choose the vast majority of network parameters to characterize the traffic in order to get a complete picture of it. As a further step toward lowering the detection time complexity, we employ the PCA approach to compress the features' dimensions. Using principal component analysis (PCA), we can save much of the original data while drastically cutting down on forecast time. After data dimensionality reduction, the RNN is used to train and get a detection model. In comparison to other approaches for detecting DDoS assaults, PCA-RNN performs much better on the real-world dataset, as shown by the evaluation results. © 2023 IEEE.

关键词： Principal component analysis

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Next Generation Firewall and Self Authentication for Network Security 7

Next Generation Firewall and Self Authentication for Network...

引用

7th international conference on Image information processing, ICIIP 2023

作者： Singh, Bhagwant Cheema, Sikander Singh Punjabi University Department of Computer Science And Engineering Punjab Patiala India

ISBN: (纸本)9798350371406

In the era of the technologies, given the importance of the prevalence of the Internet, network safety is now essential to maintaining the accessibility and confidentiality of networks and data. Regular firewalls cannot deal with new dangers including targeted and data-focused attacks. the many types of current and next-generation firewalls are covered thoroughly in this study, emphasizing their possible capabilities. the Next Generation Firewall (NGFW)'s various network security mechanisms are discussed. Additionally, the benefits of modern firewalls versus conventional firewalls were contrasted. the introduction of smartphones and widespread technology that users connect to these systems, as well as the constantly shifting model connected to global networks like the Internet, are not supported by today's authorization systems. Several of the shortcomings of a conventional authentication method will be addressed by the idea of a self-authorizing framework for authenticating in an environment that is distributed. the article discusses the main objectives of network security, current security threats, and prospective network protection measures and self-authentication. © 2023 IEEE.

关键词： Network security

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A Ginkgo Detection Algorithm in Complex Environments Based on Improved YOLOv7 9

A Ginkgo Detection Algorithm in Complex Environments Based o...

引用

9th international conference on Intelligent Computing and Signal processing, ICSP 2024

作者： Ma, Chi Guo, Qiang School of Computer Science and Engineering Huizhou University Huizhou China School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan China

ISBN: (纸本)9798350376548

Detections of Ginkgoes are prerequisites for later counting and harvesting. Due to the uneven distribution of samples, the detection speed and accuracy of existing algorithms cannot adapt to the impact of complex environments. therefore, an enhanced model YOLOv7-DC based on YOLOv7 is proposed in this paper, which redesigns the detection network and introduces a new feature fusion method. DCNv2 is embedded in the efficient layer aggregation network (ELAN), while PConv is utilized instead of conventional convolution to reduce the parameter impact of DCNv2. Moreover, the attention mechanism CBAM is introduced during training to enhance spatial and channel information, and the ConvMixer architecture is employed to capture spatial and channel relationships within the features, which are transmitted to the detection head through attention mechanism, improving the model's detection accuracy for each specific classification sample. Experimental results show that our YOLOv7-DC achieves both excellent detection speed and recognition rate in various classification tasks. the improved model's average detection accuracy is increased by 6.2% compared to previous algorithms, and the model parameters are reduced by 13%. It is proved that YOLOv7-DC is more suitable for scenarios with imbalanced samples and complex environments. © 2024 IEEE.

关键词： Classification (of information)

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Empirical Evaluation of in silico Microsatellites Mining Tools Designed Using Nextgen technology in Crops 7

Empirical Evaluation of in silico Microsatellites Mining Too...

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7th international conference on Computing, Communication and Security, ICCCS 2022 and 2022 4th international conference on Big Data and Computational Intelligence, ICBDCI 2022

作者： Umang Bharti, P.K. Husain, Akhtar Shri Venkateshwara University School of Computer Science UP Gajraula India MJP Rohilkhand University Department of CS & IT UP Bareilly India

ISBN: (纸本)9798350309904

Microsatellites are found in genome sequences of all prokaryotes and eukaryotes. they are the primary source of studying genetic variations, molecular breeding, gene discovery, disease identification, and hypervariability in a plant's genome. Many web-based and standalone computing tools have been developed to analyze sequence data using next-generation sequencing tools with several new features and objectives. Researchers always need a variety of in silico microsatellite exploring tools to analyze research data apart from extracting them. this evaluation aims to chronologically provide up-todate information on tools and databases designed explicitly to study genome-wide specifications of simple sequence repeats in crop cultivars. the study was conducted to empirically assess these tools and databases to find the next-generation technology used in designing the standalone tool, web interface & relational database. Also, to compare their processing adequateness in terms of features, such as the primer-related information, flanking sequences, statistics information of repeats, coding /non-coding, and other genomic features of the identified motif. this study may help researchers in agriculture to determine the most popular next-generation sequencing tool and technologies used to analyze microsatellite-related features and fill the gap for future applications. © 2022 IEEE.

关键词： Crops

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Research on Joint Entity-Relation Extraction for the Tibetan 'Epic of King Gesar' Based on Multi-Semantic information Fusion and Global Pointer Network 7

Research on Joint Entity-Relation Extraction for the Tibetan...

引用

7th international conference on Machine Learning and Natural Language processing, MLNLP 2024

作者： Daiqing, Zhuoma Zhang, Penghui Lang, Jie Qun, Nuo Nyima, Tashi School of Information Science and Technology Tibet University Collaborative Innovation Center for Tibet Informatization MOE and Tibet Autonomous Region Lhasa China Academy of the Zhonghuaminzu Community Tibet University Lhasa China

ISBN: (纸本)9798350354973

the 'Epic of King Gesar' is a poetic and historical Tibetan literary work and a treasure of Tibetan culture. Guided by the cultural preservation and inheritance of the Tibetan people in China, the paper deeply studies the joint entity-relation extraction method for the 'Epic of King Gesar.' Addressing issues such as redundant entities, error accumulation from traditional pipeline methods, and insufficient semantic feature capture in Tibetan, the paper proposes an entity-relation extraction method based on multi-semantic information fusion and a global pointer network. (1) CINO was used to obtain dynamic word vectors for the entire text;(2) Global and local features of the Tibetan text were extracted using BiLSTM and CNN;(3) A multi-head attention mechanism was employed to fuse the text's multiple features;(4) the OneRel decoder was used to extract entity relations. Experiments show that this method improves the F1 score by 6.80% compared to the baseline OneRel model, providing a reference for research in specific domains of minority languages in low-resource settings. © 2024 IEEE.

关键词： information fusion

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Slice-based ray casting volume shadow of volumetric datasets 7

Slice-based ray casting volume shadow of volumetric datasets

引用

7th international conference on computer Graphics and Virtuality, ICCGV 2024

作者： Luo, Dening Ma, Weixiang Guo, Dequan Chengdu University of Information Technology Chengdu610225 China

ISBN: (数字)9781510679788

ISBN: (纸本)9781510679771

the realistic volume shadow of volumetric datasets can improve the perception of shape and depth, and further enhance the efficiency of detecting defects, anomalies, and other issues. In this paper, a novel and high-performance method called slice-based ray casting (SBRC) is proposed to implement the volume shadow of volumetric datasets. the first step of the SBRC method is to use the light source as the viewpoint to render the illumination information of each slice of the volumetric datasets, slice by slice, into the illumination attenuation buffer. the second step is to use the camera as the viewpoint, render volumetric datasets using ray casting, and calculate volume shadows using the illumination attenuation buffer. the experiments show that the method can obtain much better volume shadows and more scalable performance than other volume illumination methods. this is due to the illumination attenuation calculation slice by slice and the high-efficiency shadow calculation in ray casting. And, by using a genetic algorithm, we can optimize the shadow calculation parameters in CT images to make the edges in the images clearer. © 2024 SPIE.

关键词： Genetic algorithms

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Deep Learning for Cognitive Detection based on P300 Event-Related Potential 7

Deep Learning for Cognitive Detection based on P300 Event-Re...

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7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Chaisricharoen, Roungsan Temdee, Punnarumol Srimaharaj, Wanus Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai57100 Thailand Payap University The International College Department of Information Technology Chiang Mai50000 Thailand

ISBN: (纸本)9781665495103

Due to the mechanical demands on real-time operations of brain signal reflection, manual parsing, and detection of the Event-Related Potential waveform, especially P300 evoked potential is impropriate and too slow. In addition, traditional methods require specialized knowledge and experience as well as experts to operate. therefore, a faster and easier method is essential. the application of machine learning is a very reliable and popular method for classifying large and complex data in a short time. therefore, this study presents a method to classify P300 in ERP waveforms using a deep learning algorithm which provides accurate and reliable results. It allows common and advanced users to detect the P300 evoked potential without specific skill and quickly deploy it to the BCI cases. © 2022 IEEE.

关键词： Deep learning

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the Problem of Collecting Face Recognition information in Colleges and Universities 7

The Problem of Collecting Face Recognition Information in Co...

引用

7th international conference on Communication, Image and Signal processing, CCISP 2022

作者： Feng, Zhao Judicial Expertise Center Shandong University of Political Science and Law Jinan China

ISBN: (数字)9781665459594

ISBN: (纸本)9781665459594

As China gradually enters the '5G+artificial' intelligent information era, the vigorous development of emerging technologies such as artificial intelligence, face recognition technology has been widely used to education, security and finance and other fields, at the same time, the collection of personal face recognition information is quietly leaked, caused concern and anxiety from public. In the special group of colleges and universities, the legitimacy of collecting face recognition information is controversial. this paper centers on the different expressions of collecting face recognition information in colleges and universities. © 2022 IEEE.

关键词： Face recognition

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An LSTM network-based real-time noise suppression tool for conducting audio and video conferences 7

An LSTM network-based real-time noise suppression tool for c...

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7th international conference on Computing in Engineering and technology, ICCET 2022

作者： Gosain, Aarzoo Sood, Apoorvi Department of Information Technology Netaji Subhas University of Technology Dwarka New Delhi India

ISBN: (纸本)9781839537042

Background: A real-time noise suppression tool is an essential requirement of today's time. By using such a tool, audio and video conferences can be conducted noiselessly, even in the absence of a quiet office environment. the tool's methodology includes a signal pre-processing phase and a network computations phase followed by statistical analysis. In the pre-processing phase, various signal transformation methods are analyzed comparatively. then, the most suitable one is applied to the input audio signal to extract its main frequencies. Afterward, these extracted features are used for training the deep neural network. Results: Many sample audio signals are fed to this tool, and it gives their cleaned versions with suppressed background noise. Statistical analysis for particular sample audio shows the amplitude difference between the two speech signals graphically. Conclusion: It is found that the Short-time Fourier Transform method is better amongst all other methods for extracting signal features due to its lossless nature. the backbone of the Long Short-term Memory Network facilitates this tool to retain any extended sequential information. An overall T statistic value of -94.920 for sample audio 1 and -208.843 for sample audio 2 solidifies the confidence in the accuracy of this tool. © 2022 the Institution of Engineering and technology.

关键词： Statistical methods

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