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Research on Defect Detection of Elevator Traction Steel Belt Based on YOLOv5 6

Research on Defect Detection of Elevator Traction Steel Belt...

引用

6th International conference on information communication and Signal processing, ICICSP 2023

作者： Liu, Tianyi Jiang, Xiantao Yin, Tao Cen, Qi Zhang, Zhijiang Shanghai Maritime University Dept.Information Engineering Shanghai China Ningbo Special Equipment Inpection and Research Institute Ningbo China

ISBN: (纸本)9798350339994

In order to achieve real-time detection of defects in the moving traction steel belt, a data set of traction steel cables was established and the improved YOLOv5 model was used for migration training. Image acquisition of defective samples in an environment that simulates usage scenarios. The video image data is processed, the position and category of defects are marked, and the data set is packaged. Using the principle of transfer learning, the improved YOLOv5 model is used to train on a large data set first, and then the trained model is applied to the target data set, so as to achieve anti-interference ability against complex backgrounds and maintain real-time detection. © 2023 IEEE.

关键词： defect detection elevator belt transfer learning visual detection yolov5

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Construction of Image processing Model Based on Computer Vision Algorithm

Construction of Image Processing Model Based on Computer Vis...

引用

2023 IEEE International conference on Image processing and Computer Applications, ICIPCA 2023

作者： Shao, Lin School of Media & Communication Wuhan Textile University Hubei Wuhan430073 China

ISBN: (纸本)9798350314670

As an important part of the mobile robot platform to perceive the external environment, the computer transmits the collected real-time images to the processing unit. After the image information is analyzed and processed, different functions are realized according to the actual needs. Image processing technology is a widely used technology type derived from the continuous development of computer technology. Using it in fruit detection and grading can improve the efficiency of fruit detection and grading, optimize the standard of fruit detection and grading, achieve the purpose of controlling the cost of manual detection and grading, and ensure the profit of fruit industry. We know that the human brain is the most effective biological intelligence system known, and the ability of human visual system to recognize, process and process images far exceeds any existing computer and information processing system. This paper implements image processing technology based on computer vision algorithm, so as to express the actual coordinates of objects in 3D space through 3D voxels, and can also correct the distorted images caused by projection. Compared with traditional BP neural network, image processing technology based on computer vision algorithm has more advantages and higher accuracy. © 2023 IEEE.

关键词： Grading

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MedSyn: Medical Image Synthesis of Brain Magnetic Resonance Images Based on Hybrid information Aggregation 8

MedSyn: Medical Image Synthesis of Brain Magnetic Resonance ...

引用

8th International conference on communication, Image and Signal processing, CCISP 2023

作者： Jiang, Minbo Song, Zhiwei Zhu, Chuanzhen Wang, Yi School of Computer and Control Engineering Yantai University Yantai China

ISBN: (纸本)9798350305838

Magnetic resonance imaging (MRI) is widely used in clinical scenarios. However, acquisition of certain image modalities may be in limitation due to multiple considerations such as time duration and labor costs. Hence, medical image synthesis can resolve those limitations by estimating the desired target image modality without inducing an actual scan. In this paper, we proposed a novel method which aggregated the hybrid information of MRI to improve the performance of medical image synthesis and addressed it as MedSyn. Specifically, the MedSyn adopted the GAN framework, and made some great improvement. In generator, we proposed a simple yet efficient Tri-Focus visual Center (TVC) to activate contextual features by establishing inter-dimensional dependencies with the assistance of rotation operations and gaussian functions. Furthermore, we proposed a Hybrid Global-Local Feature Extractor (HGL) module to capture long-range dependencies and exploit potential relationships between spatial and channel dimensions to extract global-local information. Benefitting from the modules of TVC and HGL jointly, the generator could capture obvious image features and underlying semantic information. In discriminator, we proposed a Dynamic Multi-Scale (DMS) Discriminator which could enhance discriminative ability by combining features of different scales dynamically. To evaluate the performance of the proposed method, we conducted experiments on three brain datasets (the Meningioma dataset, the IXI dataset and BRATS dataset), and compared the results with some state-of-the-art methods. The experimental results showed that our MedSyn outperformed other state-of-the-art methods in terms of both quantitative evaluation and qualitative visual assessments. © 2023 IEEE.

关键词： Magnetic resonance imaging

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GRU Based Multiview Summarisation to obtain fast effective Key-frame

GRU Based Multiview Summarisation to obtain fast effective K...

引用

2025 International conference on Computer, Electrical and communication Engineering, ICCECE 2025

作者： Kandaswamy, Vijay Anand Joshua Kumaresan, S. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798331513894

This paper proposes a novel approach to video summarisation by introducing a feature variance model that enhances video frame extraction. In typical video record aggregation systems, a variety of image processing tasks, such as acquisition, preprocessing, segmentation, and feature extraction, should be carried out with high precision to guarantee seamless system performance. Among these, feature extraction is essential since it breaks down large amounts of visual data into more manageable, informative vectors, and the success of the system is directly impacted by how effectively this process functions. Widely Recurrent Neural Networks (RNNs) are used in supervised video summarisation processes to obtain a model for the temporal dependencies between video frames. RNN's ability to learn long-range memory in the video is limited, and CNN often focusses on local information while losing long-term knowledge when the input sequence is lengthy. Therefore, a Gated Recurrent Unit based Neural Network (GRU-NN) for video summarisation is proposed, to classify them into keyframes and non-keyframes. Keyframes are selected for summarisation, while non keyframes are discarded or reduced. We explore various keyframe extraction techniques, analyse the performance of the proposed summarisation model, and discuss the results. Finally, we offer insights into the model's potential improvements and its broader applications in video summarisation tasks. © 2025 IEEE.

关键词： Image segmentation

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Comparative Analysis of Local Adaptive LMS Image Filtration 58

Comparative Analysis of Local Adaptive LMS Image Filtration

引用

58th International Scientific conference on information, communication and Energy Systems and Technologies (ICEST)

作者： Mironov, Rumen P. Draganov, Ivo R. Tech Univ Sofia Fac Telecommun Bulv Kl Ohridsky 8 Sofia 1000 Bulgaria

ISBN: (纸本)9798350310733

In this paper the 2D part of the developed method for local adaptive 3D filtration of multidimensional grayscale images is compared with some advanced methods for image filtrations - BM3D, Average, Gaussian and etc. The adaptation of the presented algorithm is based on the information from a small local area of the neighbouring pixels of the processed images using the developed 2D Adaptive LMS filter. A comparative analysis of the quality of the processed images was made in terms of both peak signal-to-noise ratio calculations and subjective visual quality. The experimental results were carried out with a set of test halftone images that were noised with Additive White Gaussian Noise (AWGN) with different variance levels.

关键词： Digital signal processing Local adaptive image filtration 2D LMS adaptation Image denoising

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Design of UAV Indoor Vision and UWB Integrated Inspection Algorithm 23

Design of UAV Indoor Vision and UWB Integrated Inspection Al...

引用

7th International conference on High Performance Compilation, Computing and communications, HP3C 2023

作者： Yang, Yejin Huang, Yuejin Ye, Miao Cheng, Jin Sun, Shiquan School of Information and Communications Guilin University of Electronic Technology China

ISBN: (纸本)9781450399883

This paper proposes a visual and ultra-wideband (UWB) fusion-based inspection algorithm for addressing problems of lighting, shadows, and visual blur that may occur during indoor Unmanned Aerial Vehicle (UAV) inspections. The method includes two stages: line tracking and positioning. At the line tracking stage, a downward-facing camera is used as the visual sensor for image segmentation. When an anomaly occurs in the visual sensor, it automatically switches to UWB localization and navigation mode while continuously reading the feedback from the visual sensor until it returns to normal. At the positioning stage, AprilTag and UWB are merged for location, enabling more precise UAV positioning by fusing the input results of AprilTag and UWB. Experimental results show that the proposed UAV inspection algorithm can effectively solve the problems of lighting, shadows, and visual blur that may occur during visual sensor inspection. The algorithm is based on the fusion of visual and UWB sensors, which improves system reliability and stability. © 2023 ACM.

关键词： Image segmentation

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visual communication Image Clarity processing System on the Basis of Artificial Intelligence

Visual Communication Image Clarity Processing System on the ...

引用

Data Science and information System (ICDSIS), IEEE International conference on

作者： Shuang Gao School of Fine Arts and Design Changchun Humanities and Sciences College Changchun Jilin China

ISBN: (数字)9798350381665

ISBN: (纸本)9798350381672

Traditional visual communication image processing is done manually, which is not only time-consuming and labor-intensive, but also not very effective. Therefore, this article adopted an AI (Artificial Intelligence) based visual communication image clarity processing system. The main functional modules of the system include four aspects: visual transmission of image data acquisition based on AI, adjustment of basic image parameters, image dehazing processing, and image clarity enhancement. Among them, image clarity was a complete functional module and the core of the entire image clarity processing system. This article intended to take large-scale image data as an example to analyze the computational speed and stability of the effectiveness of this method, in order to verify its practicality. The processing time for 100 images was 0.8 seconds, with a standard deviation of 0.025 for clarity improvement and 0.030 for naturalness improvement. This system is beneficial for improving the clarity of visual communication images and reducing image processing time.

关键词： visualization visual communication Image processing Data science information age Stability analysis Product design

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Recent Advances in Sign Language processing: A Focus on IoT-Based, Hybrid, and Vision-Based Approaches

Recent Advances in Sign Language Processing: A Focus on IoT-...

引用

2023 Annual International conference on Emerging Research Areas: International conference on Intelligent Systems, AICERA/ICIS 2023

作者： Joy, Anu Rose Arul Xavier, V.M. Karunya Institute of Technology and Sciences Department of Computer Science & Engineering Karunya Nagar Coimbatore India

ISBN: (纸本)9798350303452

Deaf and hard-of-hearing persons utilize sign language, a visual language. Technology development is crucial for improving communication between sign language users and non-users. Approaches that are IoT-based, hybrid, and vision-based have the potential to increase the precision, sturdiness, and accessibility of systems that process sign language. The most recent developments in IoT-based, hybrid, and vision-based sign language processing are presented in this literature review study. We highlight the potential uses of these technologies and examine the benefits and drawbacks of each strategy. Sensors and other devices are used by IoT-based sign language processing systems to gather information about the user's signs. The user may receive feedback from this data or it may be used to recognize and translate sign language gestures. IoT-based strategies are combined with other methodologies, such as deep learning and rule-based reasoning, in hybrid sign language processing systems. Computer vision techniques are used by vision-based sign language processing systems to identify and translate sign language motions from video pictures. The way sign language users interact with non-users could be completely transformed by IoT-based, hybrid, and vision-based sign language processing systems. These technologies have the potential to increase sign language's inclusivity and accessibility while also enhancing the lives of those who use it. © 2023 IEEE.

关键词： visual languages

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Research and implementation of chinese lip recognition technology based on pinyin features 3

Research and implementation of chinese lip recognition techn...

引用

3rd International conference on Advanced Algorithms and Signal Image processing, AASIP 2023

作者： Jiang, Yi Zeng, Wei Wang, Nan Xia, Huan Luo, Yuedong Zheng, Jun Chengdu University of Technology Information and Communication Engineering Szechwan Chengdu610059 China

ISBN: (纸本)9781510668522

With the development of deep learning, lip recognition technology has made great progress in English, but there is a certain gap in Chinese in both data set richness and recognition accuracy. By analyzing the visual characteristics of Chinese pronunciation, this paper puts forward the pinyin sequence of picture frames in order to avoid the ambiguity of Chinese visual expression. In order to verify the validity of pinyin sequence of picture frames, a pinyin sequence recognition model combining 3D+2D convolutional neural network with Bi-ConvLSTM and a Chinese character prediction model PPTC are proposed. Using the pinyin sequence of picture frames as the medium, the picture frames are converted into Chinese sentences. Through experiments, the superiority of the model is proved, which provides a benchmark for future work. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep learning

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Smartphone visual Assistance System with AI-Based Depth Estimation and Embedded/Cloud Voice Controls 5

Smartphone Visual Assistance System with AI-Based Depth Esti...

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5th IEEE International conference on Advanced information and communication Technologies, AICT 2023

作者： Pastukh, Volodymyr Beshley, Mykola Chopyk, Pavlo Beshley, Halyna Ivanochko, Iryna Gregus, Michal Lviv Polytechnic National University Department of Telecommunications 12 Bandery Str. Lviv Ukraine Ternopil Volodymyr Hnatiuk National Pedagogical University Faculty of Physics and Mathematics 2 Kryvonosa Str. Ternopil Ukraine Comenius University in Bratislava Department of Information Systems Bratislava Slovakia Faculty of Management Comenius University in Bratislava Department of Information Systems Bratislava Slovakia

ISBN: (纸本)9798350372571

This paper presents an advanced smartphone visual assistance system that effectively utilizes artificial intelligence (AI) to fast image depth estimation and voice control based on embedded and cloud technologies. We developed a voice control module that utilizes a combination of embedded and cloud-based APIs to improve system availability and efficiency. The proposed visual assistance system leverages the MobiNet3 neural network for object classification and the MiDaS 2 Lite model for depth estimation. In addition, we implemented an iterative asynchronous algorithm for calculating the image depth matrix, which is on average 35 times faster than the recursive approach. The test results confirm that the processing time for this algorithm is in the range from 600 μs to 2 ms. This is an important aspect to ensure the system's efficiency and accuracy in real-world use, particularly for people with visual impairments. We presented an approach that allows to determine the average values of luminance coefficients along the vertical and horizontal planes. Using grayscale values in the range from 0.0 to 1.0, we estimate the depth of the image to determine the location of objects in space and provide a spatial interpretation of the scene. © 2023 IEEE.

关键词： Smartphones

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