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检索条件"丛书名=Lecture Notes in Computer Science"

共 300226 条记录，以下是1311-1320 订阅

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A Novel Combined GAN for Defects Generation Using Masking Mechanisms 7th

A Novel Combined GAN for Defects Generation Using Masking Me...

引用

7th Chinese Conference on Pattern Recognition and computer Vision

作者： Rai, Zhiwei Li, Bo Ma, Xiaoqian Cheng, Li South Cent Minzu Univ Wuhan Peoples R China

ISBN: (纸本)9789819785049;9789819785056

Defective images generated by generative adversarial networks (GANs) often exhibit insufficiently constructed defects. The discriminator's dominance leads the generator to prioritize generating color blocks favored by the discriminator, disregarding the original information. In this paper, we propose a combined GAN that retains feature information, which comprises a defect generating GAN and a mask generating GAN. The two trained GANs are synergistically combined to generate defective images. Additionally, the structuration loss introduced in this paper guides and constrains the GAN model, aiming to preserve texture trends, grayscale distribution, and narrow defect regions. Experimental results show that our model produces high-quality images, with texture information closer to the original sample, and without the additional discriminators. This approach is evaluated against the latest detection model, demonstrating 4% improvement in effectiveness over the standard enhancement method.

关键词： Texture Information Defect Generation Combined GAN

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EPIC-Q: Equivalent-Policy Invariant Comparison Enhanced Transfer Q-learning for Run-Time SoC Performance-Power Optimization 24th

EPIC-Q: Equivalent-Policy Invariant Comparison Enhanced Tran...

引用

24th International Conference on Embedded computer Systems: Architectures, Modeling, and Simulation

作者： Surhonne, Anmol Fawzi, Haitham S. Maurer, Florian Lenke, Oliver Meidinger, Michael Wild, Thomas Herkersdorf, Andreas Tech Univ Munich Arcistr 21 D-80333 Munich Germany

ISBN: (纸本)9783031783760;9783031783777

As power density becomes the main constraint of multicore systems, managing power consumption using DVFS while providing the desired performance becomes increasingly critical. Reinforcement learning (RL) performs significantly better than conventional methods in performance-power optimization under different hardware configurations and varying software applications. RL agents learn through trial-and-error by receiving rewards which is defined by an objective function (e.g. instructions-per-second (IPS)) within specified constraints (e.g. power budget). System and application requirements lead to changing objectives and constraints which in turn result in different reward functions. The RL agents adapt to these changing objectives and constraints (and hence reward functions). Equivalent-policy invariant comparison (EPIC) is a popular technique to evaluate different reward functions. EPIC provides a numerical score which quantifies the difference in two reward functions. In this work, we use this EPIC distance (score) to transfer knowledge and improve learning for changing reward functions. Experimental results using a DVFS enabled RISCV based system-on-chip implemented on an FPGA shows 16.2% lower power budget overshoots compared to a tabular Q-learning agent with direct transfer.

关键词： EPIC DVFS reinforcement learning reward functions power management transfer learning

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Parameterized Verification of Round-Based Distributed Algorithms via Extended Threshold Automata 26th

Parameterized Verification of Round-Based Distributed Algori...

引用

26th International Symposium on Formal Methods (FM)

作者： Baumeister, Tom Eichler, Paul Jacobs, Swen Sakr, Mouhammad Volp, Marcus CISPA Helmholtz Ctr Informat Secur Saarbrucken Germany Luxembourg Univ SnT Esch Sur Alzette Luxembourg

ISBN: (纸本)9783031711619;9783031711626

Threshold automata are a computational model that has proven to be versatile in modeling threshold-based distributed algorithms and enabling their completely automatic parameterized verification. We present novel techniques for the verification of threshold automata, based on well-structured transition systems, that allow us to extend the expressiveness of both the computational model and the specifications that can be verified. In particular, we extend the model to allow decrements and resets of shared variables, possibly on cycles, and the specifications to general coverability. While these extensions of the model in general lead to undecidability, our algorithms provide a semi-decision procedure. We demonstrate the benefit of our extensions by showing that we can model complex round-based algorithms such as the phase king consensus algorithm and the Red Belly Blockchain protocol (published in 2019), and verify them fully automatically for the first time.

关键词： Consensus algorithm

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An Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstruction Accuracy 5th

An Evaluation of Low-Cost Hardware on 3D Ultrasound Reconstr...

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5th International Workshop on Advances in Simplifying Medical Ultrasound

作者： Leger, Etienne Najafi, Niki Gueziri, Houssem-Eddine Collins, D. Louis Kersten-Oertel, Marta Montreal Neuro Montreal PQ Canada Concordia Univ Montreal PQ Canada TELUQ Montreal PQ Canada

ISBN: (纸本)9783031736469;9783031736476

The advances in consumer-grade hardware, such as optical trackers and portable ultrasound machines, has paved the way for the development of more cost-effective systems. In this paper, we aimed to assess the accuracy of low-cost tracking alternatives in the context of 3D freehand ultrasound (US) reconstruction. Specifically, we compared two low-cost tracking options: a depth camera and a low-end optical tracker, to an FDA approved high-end infrared optical tracking system. Additionally, we compared two US systems, a low-cost handheld US system with a high-resolution ultrasound mobile station. Each tracker and probe pair underwent 20 acquisitions in ideal conditions. An additional 20 acquisitions were made at 3 suboptimal tracker placements. These two experiments showed no statistically significant difference between probes and no difference between the low- and high-end optical trackers on accuracy of reconstructions. As a proof of principle, we performed volume-to-volume registration using the US reconstructions and found that low-cost probe and low-cost optical tracking is similar to using the standard high cost system. These findings suggest that low-cost hardware may offer a solution in the operating room or environments where commercial hardware systems are not available without compromising on the accuracy and usability of US image-guidance.

关键词： Ultrasound Imaging Low-cost Hardware Image-guided Surgery

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A Multi-aspect Multi-granularity Pronunciation Assessment Method Based on Branchformer Encoder and Hierarchical Aggregation 31st

A Multi-aspect Multi-granularity Pronunciation Assessment Me...

引用

31st International Conference on Multimedia Modeling

作者： Du, Wenxu Wumaier, Aishan Shi, Yahui Yi, Nian Liu, Dehua Joint Int Res Lab Silk Rd Multilingual Cognit Com Urumqi Peoples R China Xinjiang Key Lab Multilingual Informat Technol Urumqi Peoples R China Xinjiang Univ Coll Comp Sci & Technol Urumqi Peoples R China

ISBN: (纸本)9789819620531;9789819620548

With the advancement of information technology, computer-Assisted Pronunciation Training (CAPT) has become an effective method for non-native(L2) speakers to learn foreign language pronunciation. However, existing automatic pronunciation quality assessment methods have not fully leveraged the inter-granularity relationships and lack further extraction of contextual features at each granularity. To address these issues, this paper proposes Bfhaformer. Bfhaformer employs an LSTM-augmented BranchFormer encoder for encoding GOP features and reference phoneme features. Compared to Transformer encoders, the BranchFormer encoder introduces parallel branch structures, which enhances the capture of local features while retaining global feature information. Additionally, this paper aggregates features across different granularities within a hierarchical model structure. By aggregating and suprasegmental feature fusion of the encoded features at pronunciation granularity such as word level and utterance level, better attention is paid to local information at the current granularity and contextual hierarchical relationships. Experiments on the publicly available Speechocean762 dataset demonstrate that our proposed method significantly improves all metrics at all granularities compared to the baseline models.

关键词： Pronunciation Assessment GOP computer-Assisted Pronunciation Training Branchformer

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A Fourier Transform Framework for Domain Adaptation 7th

A Fourier Transform Framework for Domain Adaptation

引用

7th Chinese Conference on Pattern Recognition and computer Vision

作者： Luo, Le Xu, Bingrong Zhang, Qingyong Lian, Cheng Luo, Jie Wuhan Univ Technol Sch Automat Wuhan Peoples R China

ISBN: (纸本)9789819786848;9789819786855

By utilizing unsupervised domain adaptation (UDA), knowledge can be transferred from a label-rich source domain to a target domain that contains relevant information but lacks labels. Many existing UDA algorithms suffer from directly using raw images as input, resulting in models that overly focus on redundant information and exhibit poor generalization capability. To address this issue, we attempt to improve the performance of unsupervised domain adaptation by employing the Fourier method (FTF). Specifically, FTF is inspired by the observation that the amplitude of the Fourier spectrum primarily captures low-level statistical information. In FTF, we effectively incorporate low-level information from the target domain into the source domain by fusing the amplitudes of both domains in the Fourier domain. Additionally, we observe that extracting features from batches of images can eliminate redundant information while retaining class-specific features relevant to the task. Building upon this observation, we apply the Fourier transform at the data stream level for the first time. To further align multiple sources of data, we introduce the concept of correlation alignment. We evaluate the effectiveness of our FTF method, we conducted evaluations on four benchmark datasets for domain adaptation, including Office-31, Office-Home, ImageCLEF-DA, and Office-Caltech. Our results demonstrate superior performance.

关键词： UDA Fourier Data stream alignment

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ArtSampo - Finnish Art on the Semantic Web

ArtSampo - Finnish Art on the Semantic Web

引用

21st International Conference on The Semantic Web (ESWC)

作者： Ahola, Annastiina Rantala, Heikki Hyvoenen, Eero Aalto Univ Semant Comp Res Grp SeCo Espoo Finland Univ Helsinki Helsinki Ctr Digital Humanities HELDIG Helsinki Finland

ISBN: (纸本)9783031789519;9783031789526

This paper presents first results of ARTSAMPO, a collaborative Finnish Linked Open Data (LOD) infrastructure for publishing fine art collections on the Semantic Web and for facilitating Digital Humanities (DH) research. The infrastructure consists of a Knowledge Graph (KG) whose initial version was compiled from the metadata of the three art museums of the Finnish National Gallery. A semantic ARTSAMPO portal was built on top of the KG for searching, browsing, and analyzing the underlying data. The Finnish ontology infrastructure and international datasets are used for harmonizing and enriching the data.

关键词： digital humanities fine art cultural heritage portals

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Stabilization of the Spectral Power Distribution of a Tunable Multichannel LED Lighting System 8th

Stabilization of the Spectral Power Distribution of a Tunabl...

引用

8th International Workshop on Computational Color Imaging

作者： Vernet, Sofiane Nakayama, Rei Dinet, Eric Tremeau, Alain Colantoni, Philippe Univ Jean Monnet Lab Hubert Curien 18 Rue Prof Benoit Lauras Batiment F-42000 St Etienne France Chiba Univ Inage Ward 1-33 Yayoicho Chiba 2638522 Japan

ISBN: (纸本)9783031728440;9783031728457

The advancements in Light-Emitting Diodes (LEDs) have allowed spectrally tunable light sources to gain attention in many fields of research thanks to their ability to produce a specific light output. However, LED outputs can fluctuate with temperature, and aging components can lead to noticeable discrepancies in light characteristics. This study thoroughly examines the Telelumen Dittosizer light player LED panel to exemplify a commercially available device and the associated challenges in predicting and stabilizing its output. Then, we introduce an innovative algorithm aimed at addressing such a stabilization challenge, based on a straightforward characterization procedure along with an external spectrometer. The accuracy of the algorithm was validated with different inputs, achieving a Delta(E,2000) lower than 0.5. Our findings demonstrate the ability to stabilize the spectral power distribution for a minimum of 30 min. The proposed algorithm is hardware-independent and adaptable to any combination of spectrally tunable light sources and spectrometers.

关键词： Spectrally tunable light LED lighting system Dynamic adjustment Luminous efficiency Multichannel

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Comparative Study of Federated Learning Algorithms Based on SPADE Agents 25th

Comparative Study of Federated Learning Algorithms Based on ...

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25th International Conference on Intelligent Data Engineering and Automated Learning

作者： Enguix, Francisco Peris, Saul Cerda Rincon, J. A. Carrascosa, C. Univ Politec Valencia UPV Valencian Res Inst Artificial Intelligence VRAIN Camino Vera S-N Valencia 46022 Spain Univ Burgos Dept Digitalizac Escuela Politec Super Ctra Oron 28 Burgos 09200 Spain

ISBN: (纸本)9783031777370;9783031777387

Federated Learning (FL) is a prominent method in machine learning, that ensures privacy by enabling distributed devices to collaboratively learn a shared model without exchanging local data. This paper provides a comparative analysis of various FL algorithms implemented on the Smart Python Agent Development Environment (SPADE) framework. We focus on evaluating the performance, scalability, and resilience of these algorithms across different network setups and data distribution scenarios. Our results highlight the differential impacts of decentralized versus centralized approaches, particularly under non-IID data conditions, common in real-world applications. By leveraging SPADE agents and consensus algorithms, this study not only tests algorithmic efficiency and system robustness but also explores advanced strategies like asynchronous updates and coalition-based learning, which show promise in enhancing model accuracy and reducing communication overhead.

关键词： Federated learning Multi-agent systems Consensus

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Comparative Analysis of Data Augmentation for Retinal OCT Biomarker Segmentation 11th

Comparative Analysis of Data Augmentation for Retinal OCT Bi...

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11th International Workshop on Ophthalmic Medical Image Analysis

作者： Unterdechler, Markus Fazekas, Botond Aresta, Guilherme Bogunovic, Hrvoje Med Univ Vienna Dept Ophthalmol & Optometry Christian Doppler Lab Artificial Intelligence Ret Vienna Austria

ISBN: (纸本)9783031731181;9783031731198

Data augmentation plays a crucial role in addressing the challenge of limited expert-annotated datasets in deep learning applications for retinal Optical Coherence Tomography (OCT) scans. This work exhaustively investigates the impact of various data augmentation techniques on retinal layer boundary and fluid segmentation. Our results reveal that their effectiveness significantly varies based on the dataset's characteristics and the amount of available labeled data. While the benefits of augmentation are not uniform-being more pronounced in scenarios with scarce data, particularly for transformation-based methods-the findings highlight the necessity of a strategic approach to data augmentation. It is essential to note that the effectiveness of data augmentation varies significantly depending on the characteristics of the dataset. The findings emphasize the need for a nuanced approach, considering factors like dataset characteristics, the amount of labelled data, and the choice of model architecture.

关键词： Machine Learning Data Augmentation Retinal OCT fluid segmentation

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