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检索条件"任意字段=2nd International Conference on Algorithm, Image Processing and Machine Vision, AIPMV 2024"

共 321 条记录，以下是1-10 订阅

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2024 2nd international conference on algorithm, image processing and machine vision, aipmv 2024

2024 2nd International Conference on Algorithm, Image Proces...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

ISBN: (纸本)9798350390254

The proceedings contain 76 papers. The topics discussed include: short-term forecasting of high-altitude wind fields along flight routes based on CAM-ConvLSTM 3DCNN;adaptive MSRCP-based color image enhancement method using SSA;multi-scale hybrid attention integrated with vision transformers for enhanced image segmentation;Att-CapsViT: attention-based CapsNet and vision transformer hybrid network for handwriting Chinese characters recognition;high-accuracy classification of eye diseases with pre-trained deep neural networks;abnormal clustering and cross slicing transformer for insect fine-grained image classification;Mura defect detection based on fast adaptive bidimensional empirical mode decomposition;and lightweight super-resolution reconstruction combining feature distillation and attention mechanism.

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Proceedings - 2024 2nd international conference on machine vision, image processing and Imaging Technology, MVIPIT 2024

Proceedings - 2024 2nd International Conference on Machine V...

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2nd international conference on machine vision, image processing and Imaging Technology, MVIPIT 2024

ISBN: (纸本)9798331543037

The proceedings contain 44 papers. The topics discussed include: image fusion algorithm based on frequency enhancement and shared tensor dictionary learning;research and comparison of ceramic image generation through fine-tuning stable diffusion;an attention module enhanced deep convolutional neural network for automatic hippocampus segmentation using MRI images;a few-shot learning based environmental microorganism image classification method;model pruning for infrared-visible image fusion;dual-branch and multi-scale information complementary network for hard exudates segmentation in color fundus images;an efficient lightweight network for breast cancer segmentation;and entity-enhanced question representation for knowledge-based visual question answering.

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IVCM image Enhancement Based on Improved Guided Filter 2

IVCM Image Enhancement Based on Improved Guided Filter

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Qiao, Wen Wang, Fang Yu, Hua Gao, Jiying Taiyuan University of Technology Machine Vision Shanxi Province Taiyuan China Shanxi Eye Hospital Department of Cornea Shanxi Province Taiyuan China

ISBN: (纸本)9798350390254

In order to improve the low-quality of manually captured IVCM(In Vivo Confocal Microscopy, IVCM)images, this paper proposes an IVCM image matching algorithm with guided filter enhancement based on meanshift clustering. Firstly, the original IVCM image is clustered and segmented using the meanshift algorithm, and the segmented image is used as the guiding image to realize the guided filter enhancement of the image;secondly, the key points of the neural texture of the IVCM image are extracted by the SIFT(scale-invariant feature transform)algorithm;finally, the two-step matching method is used to realize the matching of the two IVCM images. After experiments, it is proved that the proposed algorithm in this paper can extract the key information of the neural texture in the IVCM image more effectively and improve the accuracy of image alignment. © 2024 IEEE.

关键词： Wiener filtering

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A Monocular vision-based Method for In-plane Moving Target Positioning and Pose Determination 2

A Monocular Vision-based Method for In-plane Moving Target P...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Yue, Chenyang Cao, Rui Zhang, Zhixiang Liu, Boyu Wang, Binbin Li, Faxin Northwest Institute of Nuclear Technology Luoyang Xi'an710024 China

ISBN: (纸本)9798350390254

Monocular vision is a powerful method for determining the spatial position and pose of a target object. When the target trajectory is situated within the plane, we propose an approach based on monocular vision to characterize an in-plane moving target, transforming the matter into a line-plane intersection. According to the established error analysis model, the optimal observation angle (including the angle between the camera optical axis and plane) was 90°, and the analysis results verified the theoretical feasibility of our method. Simulated experiments were conducted to evaluate the accuracy of the algorithm. Compared with traditional binocular vision, the results show that the proposed method is superior in calculating the position, velocity, and pose of the in-plane moving target. The designed experiments exhibit an equivalent level of measurement accuracy. © 2024 IEEE.

关键词： error analysis monocular vision pose determination target positioning

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Multi-Scale Hybrid Attention Integrated with vision Transformers for Enhanced image Segmentation 2

Multi-Scale Hybrid Attention Integrated with Vision Transfor...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Gong, Zhaoxuan Chanmean, Meas Gu, Wenwen School of Computer Engineering Shenyang Aerospace University Liaoning Shenyang China School of Computer Science Shenyang Aerospace University Liaoning Shenyang China

ISBN: (纸本)9798350390254

In this paper, we present an advanced approach for image segmentation that enhances vision Transformers (ViTs) by integrating multi-scale hybrid attention mechanisms. While ViTs use self-attention to capture global dependencies in images, they often miss local details crucial for segmentation tasks. Our method addresses this by incorporating convolutional layers with different kernel sizes to extract local features at multiple scales. These features are then merged with the global self-attention outputs, creating a hybrid attention map that captures both fine details and overall structures. Testing on standard benchmarks shows our approach significantly improves segmentation accuracy and robustness compared to traditional ViTs, demonstrating its potential for handling complex visual scenes. © 2024 IEEE.

关键词： Convolutional neural networks

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3D Coordinate Measurement using an Optical-Probe Single-Camera vision System with an Initial Measuring Net 2

3D Coordinate Measurement using an Optical-Probe Single-Came...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Wang, Wei Guo, Lei Sun, Bo Liu, Haiqing School of Precision Instrument and Opto-electronics Engineering Tianjin University Tianjin China Technology Co. Ltd Hangzhou China

ISBN: (纸本)9798350390254

The single-camera vision measurement system based on an optical probe (a light pen) has been developed quickly and used widely in the field of 3D coordinate measurement because of its simplicity of operation, low costs, and portability. However, as the measuring space enlarges and requirements of measuring uncertainty grow, the limitations of the optical-probe single-camera 3D coordinate vision measurement system prevent it from satisfying requirements. Thus, an optical-probe single-camera vision method based on an initial net is proposed in this paper. We incorporate bundle adjustment, which is largely used in movable vision measurement. Using the proposed method, we applied a fixed-size optical probe to realize small- and large-scale measurements, maintaining the same accuracy. Experiments verified the feasibility of the proposed method. © 2024 IEEE.

关键词： Probes

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Realization of Anti-counterfeiting and Traceability of Ceramics Based on Computer vision and Blockchain Technology-Taking Jingdezhen Ceramics as an Example 2

Realization of Anti-counterfeiting and Traceability of Ceram...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Chang, Yangyang Cheng, Xien Hu, Jingfang School of Information Engineering Jingdezhen Ceramic University Jingdezhen China

ISBN: (纸本)9798350390254

Jingdezhen ceramics have a long history and are world-famous, and thus often become the object of imitation. Aiming at the current ceramic anti-counterfeiting traceability technology is not precise enough, a new treatment program is proposed. Firstly, professional equipment is used to collect the ceramic micropores, due to the randomness and uniqueness of the arrangement of micropores in the ceramic microstructure. afterwards, these micro-holes are processed by Canny edge detection method and then combined with high-precision SIFT method of computer vision for feature extraction. In the next part, this paper introduces the Interplanetary File System (IPFS) combined with decentralized and difficult to tamper with blockchain technology to write a smart contract for traceability. Finally, In the identification process, the picture to be compared with the picture stored on IPFS is compared using knnmatch, and if it meets the principle of 3 times the standard deviation, it is authentic, and vice versa, it is a fake. The experimental results show that the results can be used as a powerful basis for ceramic anti-counterfeiting traceability. © 2024 IEEE.

关键词： Micropores

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Enhancing Safety Perception in Autonomous Driving Systems Through 3D Object Detection and Neural Network Regression 2

Enhancing Safety Perception in Autonomous Driving Systems Th...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Wang, Yuhang Zhang, Yue Liu, Shutong Li, Chuangqi College of Computer and Information Engineering Henan Normal University Henan Xinxiang China School of Liberal Arts' ZhouKou Normal University Henan Zhoukou China

ISBN: (纸本)9798350390254

With the rapid development of autonomous driving technology, safety perception has become a critical component in ensuring the reliability and safety of these systems. However, challenges persist, such as traffic accidents caused by the Ideal L9, which misidentified billboard images as real vehicles, leading to erroneous emergency stops. This paper proposes a novel method to address such safety perception issues by enhancing 3D object detection accuracy. Utilizing the mmdetection framework and the SparseBEV algorithm, we identify and address deficiencies in distinguishing planar images from stereo objects. Our approach combines deep neural network regression learning with geometric constraints, introducing a hybrid discrete-continuous loss function to improve the 3D direction regression of objects. Experimental results demonstrate significant improvements in detection accuracy and safety awareness, providing a robust solution to mitigate misidentification risks. However, further optimization is needed to ensure comprehensive safety enhancement in autonomous driving systems. © 2024 IEEE.

关键词： Stereo image processing

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Research on Shaking Video image Stabilization algorithm for Moving Object Detection 2

Research on Shaking Video Image Stabilization Algorithm for ...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Wang, Chuangchuang Jia, Zhenhong Huang, Xiaohui Song, Sensen Wang, Jiajia Zhou, Gang Shi, Fei Xinjiang University Key Laboratory of Signal Detection and Processing Urumqi China

ISBN: (纸本)9798350390254

Video captured by surveillance equipment will jitter due to the shaking of the equipment, this jitter will affect the detection results of moving target detection algorithms that rely on stable video frames. This paper proposes an improved ORB algorithm to solve the video jitter problem, so that the moving target detection algorithm can accurately detect moving targets in jittery videos. First, wavelet transform is used to locate the high-frequency area of the image, and then feature extraction is performed on the area, which improves the efficiency of ORB feature extraction. And use Boosted Efficient Binary Local image Descriptor (BEBLID) to replace the descriptors of directional FAST and rotation BRIEF (ORB) to improve matching accuracy. In the feature matching stage, a neighborhood query method is proposed to replace the global search of the traditional BFMatcher, which improves the matching speed. Finally, Progressive Sample Consistency (PROSAC) is employed to ensure accurate matching of point pairs, resulting in a motion matrix for video stabilization. Finally, a Gaussian mixture model with adaptive distribution numbers is combined to quickly detect moving targets. Comparative experiments with scale-invariant feature transform(SIFT), Accelerated-KAZE(AKAZE), ORB, Qtree _ ORB and SIRB prove the superior accuracy and speed of this algorithm. © 2024 IEEE.

关键词： Wavelet transforms

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Att-CapsViT: Attention-based CapsNet and vision Transformer Hybride Network for Handwriting Chinese Characters Recognition 2

Att-CapsViT: Attention-based CapsNet and Vision Transformer ...

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2nd international conference on algorithm, image processing and machine vision, aipmv 2024

作者： Zheng, Xiangling Zhou, Nanxiang Geng, Zibin School of Information Technology & Management University of International Business and Economics Beijing China School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China

ISBN: (纸本)9798350390254

The research on text recognition has long been under the close scrutiny of scholars, especially the recognition of complex Chinese characters, which is highly favored by the academic community. In recent years, handwriting recognition has achieved remarkable results within the traditional framework of deep learning. However, this approach still falls short in capturing the subtle features and spatial hierarchical relationships within Chinese characters. Furthermore, the complexity of Chinese handwritten characters and the diversity of writing styles pose higher challenges to models. To address this, we propose an attention-based CapsN et and vision transformer hybride network for handwriting Chinese characters recognition (Att-CapsViT), which combines the attention mechanism with capsule networks and visual transformer. The Att-CapsViT model integrates the attention mechanism, combining the local detail feature capturing capability of capsule networks (CapsNets) with the global contextual awareness of visual transformer (ViT) to achieve multi-level feature extraction from local to global. This experiment was validated using two open-source datasets, successfully confirming the robust performance of the Att-CapsViT model in the recognition of Chinese handwritten characters, providing a new perspective for the field of complex text recognition. © 2024 IEEE.

关键词： Deep learning

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