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共 1490 条记录，以下是61-70 订阅

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Third International conference on Advanced Algorithms and Signal image Processing, AASIP 2023

Third International Conference on Advanced Algorithms and Si...

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3rd International conference on Advanced Algorithms and Signal image Processing, AASIP 2023

ISBN: (纸本)9781510668522

The proceedings contain 210 papers. The topics discussed include: research progress and prospects of intelligent planning algorithms in navigation collision avoidance;research on determining the end point of carbon kneading based on LSTM algorithm;pavement grade recognition algorithm based on sprung mass acceleration;research on distributed network information security diagnosis method based on matrix algorithm;two-dimensional array antenna directional pattern optimization method based on genetic simulated annealing algorithm;air defense target allocation based on improved genetic algorithm;research on visible and infrared binocular image fusion algorithm based on improved NSCT;study and application of migration technology in ground penetrating radar (GPR) data processing;load forecasting analysis based on the residential electricity consumption data;performance of BOK-MPSK chirp modulation for data transmission;and anomaly detection method of power purchase material data based on B IRCH clustering algorithm and time series.

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Discriminative Learning of Two-Dimensional Probabilistic Context-Free Grammars for Mathematical Expression recognition and Retrieval 10th

Discriminative Learning of Two-Dimensional Probabilistic Con...

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10th iberian conference on pattern recognition and image analysis (IbPRIA)

作者： Noya, Ernesto Miguel Benedi, Jose Andreu Sanchez, Joan Anitei, Dan Univ Politecn Valencia Pattern Recognit & Human Language Technol Res Ctr Valencia 46022 Spain

ISBN: (纸本)9783031048814;9783031048807

We present a discriminative learning algorithm for the estimation of two-dimensional Probabilistic Context-Free Grammars in the context of Mathematical Expressions recognition and Retrieval. This algorithm is based on a generalization of the H-criterion, as the objective function, and the growth transformations as the optimization method. In addition, experimental results are reported on the Im2Latex-100k dataset, studying the performance of the estimated models depending on the length of the mathematical expressions and the number of admissible errors in the metric used.

关键词： Discriminative learning Probabilistic Context-Free Grammars Mathematical expression retrieval Probabilistic indexing

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Interactive image Segmentation Method Based on Asymmetric Quadratic Metric 3

Interactive Image Segmentation Method Based on Asymmetric Qu...

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3rd International conference on Computer Vision and pattern analysis, ICCPA 2023

作者： Han, Benting Zhou, Shuwang Jinan250353 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Jinan250014 China

ISBN: (纸本)9781510667563

In this paper, we propose an interactive image segmentation method based on the geodesic voting model. Basically, the segmentation is implemented by thresholding a feature map generated by a geodesic voting strategy. In contrast to the classical geodesic voting method which considers isotropic metric, we exploit state-of-the-art asymmetric quadratic metric for geodesic computation. The main contribution of this work lies at an obstacle-based geodesic computation way, in order to encourage the computed geodesic paths to pass through image features of interest. The use of asymmetric quadratic metric for computing geodesic paths can take advantages from the anisotropy and asymmetry geometric features, thus overcoming the shortcuts problem suffered in the isotropic case. Experiments on real images demonstrate that the proposed method indeed can obtain promising results. © 2023 SPIE.

关键词： image segmentation

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Retrieval of Music-Notation Primitives via image-to-Sequence Approaches 10th

Retrieval of Music-Notation Primitives via Image-to-Sequence...

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10th iberian conference on pattern recognition and image analysis (IbPRIA)

作者： Garrido-Munoz, Carlos Rios-Vila, Antonio Calvo-Zaragoza, Jorge Univ Alicante UI Comp Res Alicante Spain

ISBN: (纸本)9783031048814;9783031048807

The structural richness of music notation leads to develop specific approaches to the problem of Optical Music recognition (OMR). Among them, it is becoming common to formulate the output of the system as a graph structure, where the primitives of music notation are the vertices and their syntactic relationships are modeled as edges. As an intermediate step, many works focus on locating and categorizing the symbol primitives found in the music score image using object detection approaches. However, training these models requires precise annotations of where the symbols are located. This makes it difficult to apply these approaches to new collections, as manual annotation is very costly. In this work, we study how to extract the primitives as an image-to-multiset problem, where it is not necessary to provide fine-grained information. To do this, we implement a model based on image captioning that retrieves a sequence of music primitives found in a given image. Our experiments with the MUSCIMA++ dataset demonstrate the feasibility of this approach, obtaining good results with several models, even in situations with limited annotated data.

关键词： Optical music recognition Music notation image to sequence

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Proceedings of 3rd International conference on Intelligent Engineering and Management, ICIEM 2022

Proceedings of 3rd International Conference on Intelligent E...

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3rd International conference on Intelligent Engineering and Management, ICIEM 2022

ISBN: (纸本)9781665467568

The proceedings contain 168 papers. The topics discussed include: design for ergonomics: application of single- passenger electric car via design of experiments;detection of breast cancer using machine learning and deep learning methods;automobile insurance fraud detection: an overview;a survey on detection of lung cancer using different image processing techniques;deep learning methods for automatic number plate recognition system: a review;skin cancer detection using machine learning: a survey;transforming education system through artificial intelligence and machine learning;model for retailers with price dependent demand rates;neuromarketing: an emerging domain in the formal education system;design of dual slot microstrip antenna for wireless application;analysis of ancillary services provided by distributed energy resources in smart distribution grid;and grey scale image skeletonization of vein pattern using Hausdroff image binarization technique in biometric security system.

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Digital image Conspicuous Features Classification Using TLCNN Model with SVM Classifier 10th

Digital Image Conspicuous Features Classification Using TLCN...

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10th iberian conference on pattern recognition and image analysis (IbPRIA)

作者： Rastogi, Swati Duttagupta, Siddhartha P. Guha, Anirban Indian Inst Technol Mumbai 400076 Maharashtra India

ISBN: (纸本)9783031048814;9783031048807

We present a transfer learning convolutional neural network (TLCNN) model in this study that permits classification of noticeable noise characteristics from degraded images using dispositional criteria. Various digitally degraded images comprising additive, impulsive, as well as multiplicative noise are used to test the suggested approach for noise type detection techniques. We further show that our representations sum up effectively when applied to additional datasets, achieving best-in-class results. In order to use the TL approach, we selected three CNN models: VGG19, Inception V3, and ResNet50, which are profound for visual recognition in computer vision to detect correct noise distribution. In this perplexing setting, the system's capacity to deal with the degraded image has outperformed human vision in noise type recognition. By getting noise classification performance of 99.54, 95.91, and 99.36%, while observing the nine classes of noises, the author's testing confirmed the constant quality of the recommended noise type's categorization.

关键词： Conspicuous features Noise classification CNN SVM classifier Transfer learning

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3rd International conference on Artificial Intelligence and Knowledge Processing, AIKP 2023

3rd International Conference on Artificial Intelligence and ...

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3rd International conference on Artificial Intelligence and Knowledge Processing, AIKP 2023

ISBN: (纸本)9783031686160

The proceedings contain 28 papers. The special focus in this conference is on Artificial Intelligence and Knowledge Processing. The topics include: How Do Senior Secondary Level Students and Their Teachers Perceive Artificial Intelligence and Its Implementation? An Exploratory Study;anomalous Sound pattern Detection for Machine Health Monitoring;performance Evaluation of Various Machine Learning Algorithms for Lung Cancer Prediction Using Demographic Data;enhancing Stock Portfolio Optimization Based on a Hybrid Approach Using Artificial Bee Colony Optimization and Firefly Optimization;Enhancing Yarn Quality in the Cotton Industry: AI- Based Nep Detection for Improved Manufacturing Processes;breast Cancer Diagnosis from Ultrasonic image and Histopathology image Using Deep Learning Approach;Advancing Time Series Forecasting: LSTM Networks with Multiple Attention Mechanisms;trajectory Tracking and Navigation Model for Autonomous Vehicles Using Reinforcement Learning;quantum Graph Neural Networks Based Protein-Ligand Classification;comparative analysis on Speech Driven Gesture Generation;enhancing Deep Learning: Leveraging Skip Connections and Memory Efficiency;quality-Based Decision-Making Using image Processing for Supply Chain Management;enhancing Endometrial Tumor Detection: Early Diagnosis with Advanced Vision Transformer Architecture;sweetSight: A Deep Convolutional Neural Network Approach for Automatic Categorization of Bengal Sweets;a Systematic Review: How Computer Vision is Transforming Agriculture in Economic Growth;automatic Conversion of Broadcasted Football Match Recordings to Its 2D Top View;measuring the Vehicle-in-Motion, Density and Allocation of Traffic Signal Using Transfer Learning;Ensemble Model of VGG16, ResNet50, and DenseNet121 for Human Identification Through Gait Features;Performance of Sentiment analysis APIs on Political Opinion Polling;summarization of Telugu Text Discourses;crowd-Sourced Supervisors for the Automatic Invigilation of Online

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3rd International conference on Computing and Communication Networks, ICCCN 2023

3rd International Conference on Computing and Communication ...

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3rd International conference on Computing and Communication Networks, ICCCN 2023

ISBN: (纸本)9789819708918

The proceedings contain 60 papers. The special focus in this conference is on Computing and Communication Networks. The topics include: Enhancing Security in Wireless Sensor Networks: A Broadcast/Multicast Authentication Framework with Identity-Based Signature Schemes;TSFTO: A Two-Stage Fuzzy-Based Tasks Orchestration Algorithm for Edge and Fog Computing Environments;tracking Climatic Variations Through Smart IoT-Driven Approach: An Exploratory analysis;Design and Manufacturing of an Efficient Low-Cost Fire Surveillance System Based on GSM Communications and IoT Technology;a Comparative analysis of Optimized Routing Protocols for High-Performance Mobile Ad Hoc Networks;integrating Sandpiper Optimization Algorithm and Secure Aware Routing Protocol for Efficient Cluster Head Selection in Wireless Sensor Networks;the Effects of Weather Conditions on Data Transmission in Free Space for Wireless Sensor Networks;Using Wireless Sensor Network Performance and Optimizing in Underground Mines with Virtual MIMO Antenna;a Novel Logistic Regression-Based Fire Detection Model Using IoT in Underground Coal Mines;An MQTT IoT Intrusion Detection System Using Deep-Learning;multi-objective Optimal Feature Selection for Cyber Security Integrated with Deep Learning;application of Gradient Boosting Classifier-Based Computational Intelligence to Detect Drug Addiction Threat in Society;insurance 4.0: Smart Insurance Technologies and Challenges Ahead;review on Vision Transformer for Satellite image Classification;primitive Roots and Euler Totient Function-Based Progressive Visual Cryptography;approach for Fire Detection Using image Processing;review of Various Approaches for Authorship Identification in Digital Forensics;machine Learning Model for Traffic Prediction and pattern Extraction in High-Speed Optical Networks;improved Markov Decision Process in Wireless Sensor Network for Optimal Energy Consumption.

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Different Thresholding Techniques in image Processing : A Review 1

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3rd International conference on Data Science, Machine Learning and Applications, ICDSMLA 2021

作者： Seelaboyina, Radha Vishwakarma, Rajeev Dr. A. P. J. Abdul Kalam University Indore India

ISBN: (数字)9789811959363

ISBN: (纸本)9789811959356

Document data is captured through optical scanning or digital video, resulting in a file of picture elements, or pixels, which serves as the raw input for document analysis. These pixels are samples of intensity values taken in a grid pattern throughout the document page, with intensity values ranging from OFF (0) to ON (1) for binary pictures, 0–255 for gray-scale images, and 3 channels of 0–255 color values for color images. The initial stage in document analysis is to process this image so that it may be analyzed further. Thresholding is used to convert a gray-scale or color image to a binary image, and noise reduction is used to remove superfluous data. The goal of this paper is to summarize some thresholding technique for image processing. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Binary images

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Multi-source image Matching using Improved ORB Algorithm 3

Multi-source Image Matching using Improved ORB Algorithm

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3rd International conference on Computer Vision and pattern analysis, ICCPA 2023

作者： Xu, Chao Yang, Huamin Yan, Sitong Wang, ZiYun Department of Computer Science and Technology Changchun University of Science and Technology Jilin Changchun130022 China

ISBN: (纸本)9781510667563

image matching is an essential technique in computer vision for many applications (e.g., image understanding). In order to improve the adaptability of previous matching algorithms to multi-source images (i.e., perspective and panoramic images) and increase the matching accuracy, we propose an improve Oriented FAST and Rotated BRIEF (ORB) matching algorithm. We first use the K-Nearest Neighbor (KNN) algorithm to roughly match the feature points extracted from the uniformly partitioned image grids and calculate their matching scores to obtain high scoring matching pairs. Then, we utilize the regional local consistency constraint and affine transformation verification of the Adaptive Local Affine Matching (AdaLAM) method to further refine the matching pairs. Finally, we perform matching experiments on both perspective and panoramic images and show better matching results than most previous matching approaches. © 2023 SPIE.

关键词： image matching

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