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27th International Conference on pattern recognition, ICPR 2024

ISBN: (纸本)9783031783944

The proceedings contain 958 papers. The special focus in this conference is on pattern recognition. The topics include: Supervised Mixup: Protecting the Likely Classes for Adversarial Robustness;IFFusion: Illumination-Free Fusion Network for Infrared and Visible images;infrared and Visible image Fusion Method Based on Learnable Joint Sparse Low-Rank Decomposition;Glare-SNet: Unsupervised Glare Suppression Balance Network;Learning to Detect Lithography Defects in SEM images;time-Aware Intent Contrastive Learning with Rare-Class Sample Generator for Sequential Recommendation;UAD-DPL: An Unknown Encrypted Attack Detection Method Based on Deep Prototype Learning;effects of Primary Capsule Shapes and Sizes in Capsule Networks;ASwin-YOLO: Attention – Swin Transformers in YOLOv7 for Air-to-Air Unmanned Aerial Vehicle Detection;quaternion Squeeze and Excitation Networks: Mean, Variance, Skewness, Kurtosis As One Entity;dualswin-Ynet: A Novel Bimodal Fusion Network for Ship Detection in remote sensing images;STMAE: Spatial Temporal Masked Auto-Encoder for Traffic Forecasting;BF-UNet: Bi-level Routing Attention U-shaped Network Based on Explicit Visual Prompt;learning Dynamic Representations in Large Language Models for Evolving Data Streams;attend, Distill, Detect: Attention-Aware Entropy Distillation for Anomaly Detection;pneumonia Classification in Chest X-Ray images Using Explainable Slot-Attention Mechanism;SegNet-ATT: Cross-Channel and Spatial Attention-Enhanced U-Net for Semantic Segmentation of Flood Affected Areas;WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking;detection of Oral Potentially Malignant Lesions Through Transformer-Based Segmentation Models;ROI-Aware Dynamic Network Quantization for Neural Video Compression;secureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning;TVT: Training-Free Vision Transformer Search on Tiny Datasets;one-Shot Classification Is Enough for Automatic Label Mapping;sustainable and

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27th International Conference on pattern recognition, ICPR 2024

27th International Conference on Pattern Recognition, ICPR 2...

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27th International Conference on pattern recognition, ICPR 2024

ISBN: (纸本)9783031784941

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27th International Conference on pattern recognition, ICPR 2024

27th International Conference on Pattern Recognition, ICPR 2...

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27th International Conference on pattern recognition, ICPR 2024

ISBN: (纸本)9783031781186

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27th International Conference on pattern recognition, ICPR 2024

27th International Conference on Pattern Recognition, ICPR 2...

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27th International Conference on pattern recognition, ICPR 2024

ISBN: (纸本)9783031783463

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Research on feature point generation and matching method optimization in image matching algorithm

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WIRELESS NETWORKS 2021年 1-14页

作者： Jiang, Xiaobo Yu, Jun Jiang, Jianhua Guangdong Polytech Sci & Technol Zhuhai Guangdong Peoples R China

image matching is a basic problem in image processing and pattern recognition. It is used to calculate the visual similarity between images taken in the same scene with different sensors, different perspectives or at different times. In addition to image adjustment, it is an indispensable step in image analysis and digital photogrammetry. It is also important for applications such as automatic navigation, image processing, medical image analysis, and motion estimation. The current image adjustment technology can be divided into three categories: domain-based image conversion technology, gray-scale-based technology, and performance-based technology. Among them, the feature-based matching algorithm directly matches the features of the image, so it greatly improves the calculation efficiency and is easy to adapt to complex image transformations, such as geometric distortion, different resolutions, and image transformations at different angles. image matching refers to the process of using effective matching algorithms to find the same or similar cue points for two or more image data. In applications such as medical image processing and analysis, remote sensing monitoring, weapon movement and image processing, image matching technology is an important step. images have strong structural features, such as corners, edges, statistics, and textures. These functions play an important role in image matching and scanning technology. The key to many image matching problems depends on selection, detection and expression. For different image matching problems, different functions are selected, and the matching results may be very different.

关键词： image matching algorithm Feature point generation Matching method Optimization research

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27th International Conference on pattern recognition, ICPR 2024

27th International Conference on Pattern Recognition, ICPR 2...

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27th International Conference on pattern recognition, ICPR 2024

ISBN: (纸本)9783031781711