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检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4811 条记录，以下是111-120 订阅

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Race Swing Prediction and Importance Analysis Based on LSTM Recurrent Neural Network and Random Forest Algorithm 2

Race Swing Prediction and Importance Analysis Based on LSTM ...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Tan, Haorui Maynooth International Engineering College Fuzhou University Fuzhou China

ISBN: (纸本)9798350360240

Contest swings are influenced by multiple and complex factors, which makes accurate prediction a challenging task. This study aims to utilize the advanced LSTM recurrent neural network with the random forest algorithm to make predictions of race swings and analyze the related important factors in depth. The experimental results show that the LSTM recurrent neural network can effectively capture the swings occurring in the contest and the high accuracy of the model is confirmed through relevant metrics. In addition, the analytical results of the random forest model not only determine the importance of each factor to the fluctuation of the competition but also propose corresponding coping strategies, which provide an important reference basis for further coping with the fluctuation. These findings provide important empirical support for a deeper understanding of the complexity of race swings and the development of effects. © 2024 ieee.

关键词： Prediction models

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Citizen Hotline Text Categorization Based on Short Text Extension and Feature Fusion 2

Citizen Hotline Text Categorization Based on Short Text Exte...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Zheng, Dongyu University International College Macau University of Science and Technology Macau China

ISBN: (纸本)9798350360240

The citizen hotline is characterized by short text and sparse features. This paper proposes a short text expansion method and a text classification model based on dual channel feature fusion by BiGRU and BGTC, which realizes the automatic recognition and classification of citizen hotline texts. Firstly, TF-IWF model and LDA topic model are used to build the core thesaurus;Then, Word2Vec is used to calculate the word similarity and complete the expansion of short text content and word vector features;Finally, the extended text classification is realized through the BGTC model that integrates the feature information of TextCNN and BERT BiGRU Attention channels. Through several groups of comparative experiments, the results show that the method has better performance in the text classification task of citizen hotline, with the accuracy and F1 value reaching 85.6% and 85.8% respectively. © 2024 ieee.

关键词： Classification (of information)

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Research on the Application of Object Detection Algorithm Based on Deep-Learning in Photo Management System 2

Research on the Application of Object Detection Algorithm Ba...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Haiyan, Zheng Ruili, Zhang Weijun, Chen Zuoxin, Ge Institute of Information Engineering Qingdao Hengxing College of Science and Technology Qingdao China Qingdao Campus of Naval Aeronautical University Department of Aviation Equipment Support and Command Qingdao China School of International Education Qingdao Hengxing College of Science and Technology Qingdao China

ISBN: (纸本)9798350360240

Traditional image management adopts manual comparison between the real situation after maintenance and the photos in the standard atlas, which has a large maintenance workload and inaccurate detection effect. In view of this situation, this paper puts forward a method of comparing photos with the YOLO V4 algorithm using deep-learning, which uses self-made data set to train the model. A comparative analysis is carried out with the previous algorithm. The research results show that the method with YOLO V4 algorithm can achieve better results in the average accuracy of photo comparison. © 2024 ieee.

关键词： Contrastive Learning

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Map Activation Quantization for image Classification with Limited Data 2

Map Activation Quantization for Image Classification with Li...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Li, Xiaohui Wu, Qi Zhang, Wentao Tan, Zhijun Wang, Ruixuan Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350360240

Deep learning applications in image classification often rely on extensive training data. However, in specific scenarios, obtaining a substantial amount of training data poses significant challenges. Training models with limited data often leads to overfitting and poor generalization performance. To address this issue, we propose a novel method based on map activation quantization for image classification. Our method quantizes spatial activations of latent representations, modeling the relationship between discrete representations and categories. This effectively captures variations in object properties, providing more reliable classification information and mitigating overfitting in scenarios with limited data. Furthermore, our approach seamlessly integrates with any convolutional neural network model without necessitating alterations to existing architectures or methodologies. Empirical evaluations on natural and medical image datasets demonstrate the superiority of our method in image classification under limited data scenarios, establishing a new technological benchmark. We intend to publicly release the relevant source code. © 2024 ieee.

关键词： Convolutional neural networks

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Bearing Fault image Recognition Method Based on Decision Fusion and Optimization Deep Learning Framework 2

Bearing Fault Image Recognition Method Based on Decision Fus...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Yan, Hanjun Software Engineering Institute Jiangxi University of Software Professional Technology Nanchang China

ISBN: (纸本)9798350360240

Classical algorithms in data mining have been widely studied and applied in industrial equipment condition monitoring. However, the traditional deep learning models are not yet accurate in identifying the bearing status, and most of them rely on manual experience for identification, which leads to certain errors. This study proposes a hyperparameter optimization method using a swarm optimization algorithm for CNN architecture. At the beginning, the primary vibration signal is converted into a two-dimensional time-frequency map to construct a dataset. Second, the network noise immunity is tested and the optimal network framework is determined. Then, the parameter search is optimized using the swarm optimization algorithm and the fitness function is designed. Finally, the interpretability and stability of the network are improved by visualization and decision fusion. After the verification of Case Western Reserve University bearing dataset, the method introduced in this research paper displays noteworthy accuracy in fault diagnosis and holds substantial significance for engineering applications. © 2024 ieee.

关键词： Convolutional neural networks

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Study on Digital Construction System of Changbai Mountain Manchu Paper-Cut by computer Application of image processing Technology 2

Study on Digital Construction System of Changbai Mountain Ma...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Zheng, Hanyu Changchun University of Architecture and Civil Engineering Jilin Changchun China

ISBN: (纸本)9798350360240

In order to solve the problems of digital expression, content retrieval and cultural calculation of traditional Manchu paper-cut patterns in Changbai Mountain area, an XML-based information storage model was proposed. This method can not only transform paper-cut images into XML format, but also provide the basis for paper-cut content retrieval, data mining and cultural operation. The deformation technique of TPS image and the MLS transform technique based on surface are presented. Take the input decoupage as the source image, and take a photo that needs to be generated decoupage style as the target image, the source image is deformed by the deformation algorithm according to the calibrated feature points to obtain the paper-cut style painting with the characteristics of the target image. The validity and advantages of the existing cultural rule mining methods are evaluated by verifying them. The experiment proves that by adding the required structure and characteristics, the constructed database can provide support for data mining and humanistic computing. The design ideas of the model in this paper are also applicable to other non-text resources. © 2024 ieee.

关键词： Application programs

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A Corpus System Study of Oral English Ability Improvement Based on Big Data Analysis 2

A Corpus System Study of Oral English Ability Improvement Ba...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Zhang, Hui School of International Education Chengdu Agricultural College Chengdu China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350360240

This paper presents a project that utilizes the WECCL (Chinese learners' oral English level) and COCA (native English speakers' corpus) datasets. Focusing on Chinese English learners and native English speakers, the project combines the SELL corpus with virtual reality to create an English learning and communication network platform. The system's hardware employs an ARM chip as the control center and TDA7498ETR in the sensor component for sound amplification. NRF24L01 is used for reading and writing language data to enrich the database. The platform establishes different output channels for sound signal output through retrieval and editing layers. Experimental results indicate that the developed deep neural network exhibits higher speech diversity, more accurate simulated speech, and stronger generalization in practice. The system facilitates AI character communication in various scenarios, enhancing learners' oral ability and language knowledge. © 2024 ieee.

关键词： Adversarial machine learning

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引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Su, Yueyao International College Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9798350360240

Fourier transform as a mathematical tool plays an important role in timbre recognition technology because of its ability to realize the conversion of time domain signals into frequency domain signals so that sounds can be parametrically analyzed according to their frequencies and perform timbre feature extraction to achieve timbre similarity recognition and classification. This paper analyzes and composes the principles and practical applications of Fourier transform in multi-dimensional timbre feature extraction according to the current research status. This paper will first introduce the basic theory of musical timbre similarity recognition, i.e., the definition of timbre and the main steps of timbre recognition, focusing on one of the most important steps of timbre recognition - the timbre feature extraction stage. Secondly, this paper makes a comparative study on the principle of using Fractional Fourier Transform (FRFT), Fast Fourier Transform (FFT), Short-term Fourier Transform (STFT) descriptors in the Mel Frequency Cepstrum Coefficient (MFCC), and the Infinite Impulse Response Constant Q Transformation (IIR-CQT). Then this research analyzed and compared the performance of these methods using Fourier transform to extract timbre features. © 2024 ieee.

关键词： Frequency domain analysis

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A Retrieval Method Based on Multimodal Pedestrian Features 2

A Retrieval Method Based on Multimodal Pedestrian Features

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Li, Yongjie Xie, Shaobin School of Computer Science Guangdong University of Foreign Studies South China Business College Guangzhou510545 China

ISBN: (纸本)9798350360240

In this paper, we propose a retrieval method based on Multimodal Pedestrian Features. This method aims to combine pedestrian attribute features, as described in text, with video images to automatically search for and recognize pedestrians with specific attributes within a video stream. The recognition accuracy is enhanced through the use of a partitioning method for problem modeling, which decomposes the video into smaller, more manageable subproblems. Keywords are extracted using encoders and decoders, facilitating the multimodal fusion of data by integrating image algorithms that process pedestrian attributes with natural language processing algorithms that interpret textual descriptions. The proposed method has potential applications in the fields of video surveillance, crowd analysis, and public safety, offering an efficient and intuitive approach to quickly locate and identify specific individuals from extensive video data, thereby improving recognition efficiency. © 2024 ieee.

关键词： Natural language processing systems

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Research on E-Commerce image Recognition Search Engine Optimization System Based on computer Artificial Intelligence 2

Research on E-Commerce Image Recognition Search Engine Optim...

引用

2nd ieee international conference on image processing and computer applications, icipca 2024

作者： Wang, Daocai Chongqing Electronic Information College Chongqing China

ISBN: (纸本)9798350360240

This paper proposes an electronic commerce system based on Java platform. The main content of the platform is to obtain the user's interest characteristics, build the model and calculate the similarity. This paper generates a preliminary proposal template and set thresholds during data processing. The vector space modeling method is used to classify different types of goods. By using the joint optimal convolutional neural network based on SoftMax Loss and Triplet Loss, a ternal embedded tag structure is constructed to realize similarity detection at each level. Using WebLogic technology and J2EE architecture to achieve all business logic and load balance. The JSP/Servlet web program has been loaded into the web container. An entity Beans is deployed in the EJB container. The results show that this method can not only achieve better classification performance, but also improve the image retrieval accuracy of different levels of label structures on fine-grained data sets. This is of great significance in the recommendation of related products in e-commerce. © 2024 ieee.

关键词： Search engines

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