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检索条件"任意字段=Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition"

共 692 条记录，以下是91-100 订阅

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ApproxCT: Approximate Clustering Techniques for Energy Efficient Computer Vision in Cyber-Physical Systems 12

ApproxCT: Approximate Clustering Techniques for Energy Effic...

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12th international conference on Open Source Systems and Technologies (ICOSST)

作者： Javed, Raja Haseeb Siddique, Ayesha Hafiz, Rehan Hasan, Osman Shafique, Muhammad Natl Univ Sci & Technol Sch Elect Engn & Comp Sci Islamabad Pakistan ITU Lahore Pakistan Vienna Univ Technol Inst Comp Engn Vienna Austria

ISBN: (纸本)9781538695647

the emerging trends in miniaturization of Internet of things (IoT) have highly empowered the Cyber-Physical Systems (CPS) for many social applications especially, medical imaging in healthcare. the medical imaging usually involves big data processing and it is expedient to realize its clustering after data acquisition. However, the state-of-the-art clustering techniques are compute intensive and tend to reduce the processing capability of battery-driven or energy harvested IoT based embedded devices (e.g., edge and fogs). thus, there is a desire to perform energy efficient implementation of the machine learning based clustering techniques. Since, the clustering techniques are inherently resilient to noise and thus, their resilience can be exploited for energy efficiency using approximate computing. In this paper, we proposed approximate versions of the widely used K-Means and Mean Shift clustering techniques using the state-of-the-art low power approximate adders (IMPACT). the trade-off between power consumption and the output quality is exploited using five well-known pattern recognition datasets. the experiments reveal that K-Means algorithm exhibits more error resilience towards approximation with a maximum of 10% - 25% power savings.

关键词： Cyber-Physical Systems Internet of things Approximate computing Clustering Low Power Approximate Adders Energy Consumption Computer Vision

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Algorithms of the Cluster and Morphological Analysis for Mineral Rocks recognition in the Mining Industry 12th

Algorithms of the Cluster and Morphological Analysis for Min...

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12th international conference on Intelligent computing (ICIC)

作者： Baklanova, Olga E. Baklanov, Mikhail A. D Serikbayev East Kazakhstan State Tech Univ Ust Kamenogorsk Kazakhstan Tomsk State Univ Tomsk Russia

ISBN: (纸本)9783319422947;9783319422930

this paper describes an algorithm for automatic segmentation of color images of various ore types, using the methods of morphological and cluster analysis. there are some examples illustrating the usage of the algorithm to solve mineral recognition problems. the effectiveness of the proposed method lies in the area of automatic objects of interest identification inside the image, tuning the parameters of the amount allocated to the segments. this paper contains short description of morphological and cluster analysis algorithms for the mineral recognition in the mining industry.

关键词： pattern recognition Segmentation of color images Cluster analysis Morphological analysis Mineral rocks Mining industry

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Class relevant pattern mining in output-polynomial time

Class relevant pattern mining in output-polynomial time

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12th SIAM international conference on Data Mining, SDM 2012

作者： Grosskreutz, Henrik Fraunhofer IAIS Schloss Birlinghoven 53754 Sankt Augustin Germany

ISBN: (纸本)9781611972320

the set of so-called relevant patterns is a subset of all itemsets particularly suited for pattern-based classifica- Tion tasks. So far, no efficient algorithm has been de- veloped for computing the set of relevant patterns: All existing solutions have a worst-case complexity which is exponential in the size of the input and output. In this paper, we investigate new properties of the relevant pat- Terns and develop, thereupon, the first algorithm whose runtime is polynomial in the size of the input and out- put. As we show in the experimental section, this result is not only of theoretical interest but also of practical importance, often reducing the search space by orders of magnitude. Copyright © 2012 by the Society for Industrial and Applied Mathematics.

关键词： Polynomial approximation

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Application of the image detection technology on dairy goat management 12

Application of the image detection technology on dairy goat ...

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12th international conference on Awareness Science and Technology, iCAST 2023

作者： Wang, Jia-Wen Chen, Jr-Shian Yang, Wei-Zhu Department of Information Management Chaoyang University of Technology Taichung Taiwan College of Computing and Informatics Providence University Taichung Taiwan Department of Information Management Nanhua University Chiayi Taiwan

ISBN: (纸本)9798350324693

the identification of goat breeds in dairy farms often relies on the experience of breeders. However, the traditional method of manual breed identification requires significant training and depends on the professional experience of breeder. this process is time-consuming and can lead to misjudgments, particularly when the breeder lacks experience. To address these challenges, this study applied YOLO technology to conduct research on the detection and classification of goat breeds. Several advantages were observed in this study: (1) the augmentation technique was integrated with the YOLO model, and the anchor boxes were adjusted by k-means to improve the recognition accuracy;(2) the knowledge and research data were collected from breeders in a dairy goat farm located in southern Taiwan. (3) the results demonstrated a substantial improvement in average precision (AP) values, with mAP reaching 90.14%. Based on the findings, the outcomes of this research are expected to serve as a valuable reference for future studies on classification and detection technologies. © 2023 IEEE.

关键词： Object detection

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2023 IEEE 12th international conference on Cloud Networking, CloudNet 2023

2023 IEEE 12th International Conference on Cloud Networking,...

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12th IEEE international conference on Cloud Networking, CloudNet 2023

ISBN: (纸本)9798350313062

the proceedings contain 68 papers. the topics discussed include: efficient algorithms for obnoxious facility location on a line segment or circle;vehicular edge computing-driven optimized multihop clustering with data aggregation;cloud telescope: a distributed architecture for capturing internet background radiation;a multi-stakeholder cloud-continuum framework for 6G networks security & service management;unveiling equity: exploring feature dependency using complex-valued neural networks and attention mechanism for fair data analysis;RoMA: resilient multi-agent reinforcement learning with dynamic participating agents;attribute-based searchable proxy re-encryption blockchain data sharing scheme;and a sensor predictive model for power consumption using machine learning.

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12th international Congress in Telematics and computing, WITCOM 2023

12th International Congress in Telematics and Computing, WIT...

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12th international Congress in Telematics and computing, WITCOM 2023

ISBN: (纸本)9783031453151

the proceedings contain 35 papers. the special focus in this conference is on Telematics and computing. the topics include: A Novel Method Based on Gunnar Farneback Method, Mathematical Morphology, and Artificial Vision for Flow Analysis in Electrochemical Reactors;search Space Reduction in Road Networks for the Ambulance Location and Allocation Optimization Problems: A Real Case Study;development of a Web-Based Calculator to Simulate Link Budget for Mobile Communications Systems at Urban Settlements;scientific Information Management System for Multidisciplinary Teams;air Quality Prediction in Smart Cities Using Wireless Sensor Network and Associative Models;User Interface of Digital Platforms Used TDHA Patients: Case Study in Educational Environment;recognition of Pollen-Carrying Bees Using Convolutional Neural Networks and Digital Image Processing Techniques;enhancing Air Quality Monitoring in Mexico City: A Hybrid Sensor-Machine Learning System;multi-labeling of Malware Samples Using Behavior Reports and Fuzzy Hashing;APOS is Not Enough: Towards a More Appropriate Way to Estimate Computational Complexity in CIC Decimation Architectures;Computational Simulation Applied to 3.5 GHz Band Microstrip Yagi Array Antenna Design for 5G Technology Mobile Wireless Device;3D Point Cloud Outliers and Noise Reduction Using Neural Networks;Development and Coding of a Data Framing Protocol for IoT/LPWAN Networks Based on 8-Bit Processing Architectures;performance Analysis of Variable Packet Transmission Policies in Wireless Sensor Networks;about a Sentiment Analysis Technique on Twitter and Its Application to Regional Tourism in Quintana Roo;comparative Study of pattern recognition Techniques in the Classification of Vertebral Column Diseases;security Verification of Instant Messaging Cryptographic Protocols;Elaboration of an Information System to Improve Operational Discipline in PEMEX with LAGS Methodology;ICIS: A Model for Context-Based Classification of Sensitive Personal In

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A Picture of the Growing ICER Community 16

A Picture of the Growing ICER Community

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12th ACM Annual conference on international computing Education Research (ICER)

作者： Simon Univ Newcastle Callaghan NSW 2308 Australia

ISBN: (纸本)9781450344494

this bibliometric study examines the authorship of the papers presented at ICER since the conference began in 2005. It finds that the pattern of authorship complies well with Lotka's law, an accepted model of author distribution within a discipline. ICER's most prolific authors are identified and their contributions quantified, along with measures of the collaborations between authors. New authors are found to be joining the community at a steady rate, some beginning as co-authors with established community members and some joining alone or with other new authors. the analysis extends to the contributions from different countries. the conclusion is that the community of ICER authors is truly international, has a solid core around which excellent growth is evident, displays strong collaboration, and has at least one of the characteristics of a full-fledged discipline.

关键词： computing education research author productivity bibliometrics

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Semantic Filtering Global and Local Embeddings Fusion for Few-Shot Image Classification 12

Semantic Filtering Global and Local Embeddings Fusion for Fe...

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12th international conference on computing and pattern recognition, ICCPR 2023

作者： Nong, Luyu Wu, Min Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China

ISBN: (纸本)9798400707988

Neural networks have demonstrated superior performance in image classification tasks, however, acquiring sufficient labeled data for training them in real-world scenarios remains challenging. Few-shot learning (FSL) was proposed to address this challenge in low-data scenarios and has attracted considerable attention in recent years. In few-shot image classification tasks, most of the existing FSL methods focus on designing discriminative network structures for exploring image features, either neglecting semantic information that is crucial for accurate classification, or tending to prioritize either global or local image features. To address this issue, we propose in this work a novel model Semantic Filtering Global and Local embeddings for fusion (SFGL) for few-shot image classification. SFGL effectively integrates both global and local features while leveraging semantic information. Extensive experiments conducted on benchmark datasets demonstrate that our proposed SFGL model outperforms state-of-the-art methods in FSL tasks. © 2023 ACM.

关键词： Image classification

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A Comparative Study of ConvNets based on Finger Vein Biometrics 7

A Comparative Study of ConvNets based on Finger Vein Biometr...

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7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Chavan, Anuj Arora, Prerna Raghuwanshi, Ishika Kulkarni, Sujata Sardar Patel Institute of Technology Department of Electronics and Telecommunication Mumbai India

ISBN: (纸本)9798350397253

Gaining extraordinary attention in recent years, Finger Vein Biometrics has an ideal viability with the advantages of being the least susceptible to identity theft and being present inside the body, making it difficult to forge and be affected by any external factors. Although methods of extracting information from the veins are still under investigation, one of the critical stages of biometrics is recognition and matching to the individual under test. It is carried out with techniques of explicit feature extraction, which add to the extra computation and are hence deprecated and unnecessary. pattern-matching methods using feature extraction techniques add to the time and memory complexity of the models. Instead, one can use machine learning models, like CNNs and 'commercial ConvNets' (MobileNET, ResNET, DenseNET, etc.), to obtain an automated feature map for pattern matching with high accuracy. this article presents specially customized CNNs to achieve high matching accuracy for finger vein recognition and compares performance with commercial ConvNET models. © 2023 IEEE.

关键词： pattern matching

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Analyzing the influence of pitch quantization and note segmentation on singing voice alignment in the context of audio-based Query-by-Humming 12

Analyzing the influence of pitch quantization and note segme...

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12th international conference on Sound and Music computing, SMC 2015

作者： Valero-Mas, Jose J. Salamon, Justin Gómez, Emilia Pattern Recognition and Artificial Intelligence Group University of Alicante Spain Music and Audio Research Laboratory New York University United States Music Technology Group Universitat Pompeu Fabra Spain

ISBN: (纸本)9780992746629

Query-by-Humming (QBH) systems base their operation on aligning the melody sung/hummed by a user with a set of candidate melodies retrieved from polyphonic songs. While MIDI-based QBH builds on the premise of existing annotated transcriptions for any candidate song, audiobased research makes use of melody estimation algorithms for the songs. In both cases, a melody abstraction process is required for solving issues commonly found in queries such as key transpositions or tempo deviations. Full automatic music processes are commonly used for this, but due to the reported limitations in state-of-the-art methods for real-world queries, other possibilities should be considered. In this work we explore three different melody representations, ranging from a general time-series one to more musical abstractions, which avoid full automatic transcription, in the context of an audio-based QBH system. Results show that this abstraction process plays a key role in the overall accuracy of the system, obtaining the best scores when temporal segmentation is dynamically performed in terms of pitch change events in the melodic contour. © 2015 Jose J. Valero-Mas et al.

关键词： Transcription

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