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

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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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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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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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New trends in musical genre classification using optimum-path forest

New trends in musical genre classification using optimum-pat...

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12th international Society for Music Information Retrieval conference, ISMIR 2011

作者： Marques, C. Guilherme, I.R. Nakamura, R.Y.M. Papa, J.P. Dep. of Statistics Applied Math. and Computation UNESP - Univ Estadual Paulista Rio Claro SP Brazil Department of Computing UNESP - Univ Estadual Paulista Bauru SP Brazil

ISBN: (纸本)9780615548654

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and collective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster for some applications. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have executed an experiment using very recent hybrid feature selection techniques based on OPF to speed up feature extraction process. © 2011 international Society for Music Information Retrieval.

关键词： Feature extraction

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Computation Offloading in Mobile Edge computing-Enabled Blockchain using Matching and Contract theory 12

Computation Offloading in Mobile Edge Computing-Enabled Bloc...

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12th international conference on Networks, Communication and computing (ICNCC)

作者： Li, Yijun Chen, Liming Zhang, Wenjie Zheng, Yifeng Lin, Ziqiong Minnan Normal Univ Sch Comp Sci Zhangzhou 363000 Fujian Peoples R China Fujian Med Univ Zhangzhou Afffliated Hosp Zhangzhou 106335 Fujian Peoples R China

ISBN: (纸本)9798400709265

the application of blockchain technology on mobile devices requires significant computing resources. However, the limited capacity of mobile devices cannot meet the high computing power requirements of blockchain technology, which limits the development of blockchain technology. Mobile Edge computing (MEC) is capable of alleviate the limited computing capacity of IoT terminals. this paper introduces an edge computing-enabled blockchain system consisting of an edge computing allocation center (ECAC), multiple edge service providers (ESPs), and multiple miners. To efficiently allocate resources between these miners and ESPs, we propose a hierarchical computation offloading strategy based on contract theory and matching game. During contract design phase, ECAC designs a contribution-reward contract to attract ESPs to join the trading market, and provide services to miners. By analyzing the attributes and conditions of feasible contracts of feasible contract, the optimal contract is devised using Lagrange multiplication. During matching phase, an iterative matching algorithm (IMA) is proposed to achieve the matching between ESPs and miners by constructing preference sets for miners and ESPs. Both the stability and convergence have been proved by theoretical analysis. Finally, we conduct experiments to validate the feasibility and effectiveness of the design contract. Experimental results also demonstrate the stability of IMA matching algorithm.

关键词： Mobile edge computing Blockchain Matching theory Contract theory Information scenario

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2013 IEEE/ACIS 12th international conference on Computer and Information Science, ICIS 2013 - proceedings

2013 IEEE/ACIS 12th International Conference on Computer and...

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2013 IEEE/ACIS 12th international conference on Computer and Information Science, ICIS 2013

ISBN: (纸本)9781479901746

the proceedings contain 96 papers. the topics discussed include: a study of requirement definition in user-oriented virtual network architecture;approaches to analyze requirements of billing management for cloud computing services;instant distributed minimum diameter tree construction for scalable application layer multicast;adaptation of region growing thresholds using the memetic programming algorithm;a framework for evaluating software design pattern specification languages;analysis of impression received from reverse perspective illusion to create innovative advertising;analysis of programming competency for PEAS system innovation - PEAS system: programming experience assessment scale system;layout-tree-based approach for identifying visually similar blocks in a web page;mapping of nearest neighbor for classification;and developing an argumentation support system for face-to-face collaborative learning.

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proceedings of the 12th international Workshop on Hardware and Architectural Support for Security and Privacy, HASP 2023

Proceedings of the 12th International Workshop on Hardware a...

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12th international Workshop on Hardware and Architectural Support for Security and Privacy, HASP 2023, held in conjunction with the 56th international Symposium on Microarchitecture, MICRO 2023

ISBN: (纸本)9798400716232

the proceedings contain 11 papers. the topics discussed include: SEIF: augmented symbolic execution for information flow verification;EntryBleed: a universal KASLR bypass against KPTI on Linux;Triton: software-defined threat model for secure multi-tenant ml inference accelerators;automated security analysis for real-world IoT devices;DINAR: enabling distribution agnostic noise injection in machine learning hardware;DeMiST: detection and mitigation of stealthy analog hardware trojans;data processing unit’s entry into confidential computing;towards a formally verified security monitor for VM-based confidential computing;SoK: a first order survey of quantum supply dynamics and threat landscapes;and a gem5 based platform for micro-architectural security analysis.

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2023 12th international conference on Image Processing theory, Tools and Applications, IPTA 2023

2023 12th International Conference on Image Processing Theor...

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12th international conference on Image Processing theory, Tools and Applications, IPTA 2023

ISBN: (纸本)9798350325416

the proceedings contain 45 papers. the topics discussed include: skin cancer classification using levy stable based ensemble and it’s real-time implementation on OpenVINO toolkit;effects of region of interest location on osteoarthritis detection using deep feature learning;invariant convolutional networks;an order and difference local binary pattern for hyperspectral texture classification;leveraging transfer learning for analyzing cattle front teat placement;animated lightning bolt generation using machine learning;and CNN ensemble robust to rotation using radon transform.

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the alpha-procedure as an inductive approach to pattern recognition and its connection with lorentz transformation 12th

The alpha-procedure as an inductive approach to pattern reco...

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12th international Scientific and Technical conference Computer Science and Information Technologies, CSIT 2017

作者： Lange, Tatjana University of Applied Sciences Merseburg06217 Germany

ISBN: (纸本)9783319705804

the paper deals with problems which appear when solving the task of pattern recognition in a feature space that is not identical with the space of the unknown decisive key features. In a common sense it deals with the correctness of solutions which are found in different coordinate systems. Even more, the opportunity of constructing a feature space for the final separation of classes by selecting the features in pairs, how it is done by the Alpha-procedure, will be investigated. thereby, the problem of stability during the solving of pattern recognition tasks will be considered from the point of view of transformation groups. the possibility of avoiding the necessity of regularization by using the geometric equiaffine Lorentz transformation will be shown, exploiting for that aim as example the alpha-procedure. © 2018, Springer international Publishing AG.

关键词： Mathematical transformations

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