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检索条件"任意字段=Lecture Notes in Computer Science"

共 135245 条记录，以下是921-930 订阅

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Leveraging Pruning, Quantization and Multi-objective Optimization for an Efficient Deployment of Multi-modal Models 31st

Leveraging Pruning, Quantization and Multi-objective Optimi...

引用

31st International Conference on Multimedia Modeling, MMM 2025

作者： Vu, Dang Dang, Tien Nguyen, Quoc-Trung Pham, Tan Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam FPT Software AI Center Ho Chi Minh City Viet Nam AISIA Lab Faculty of Mathematics and Computer Science Ho Chi Minh City Viet Nam Faculty of Computer Science University of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789819620739

The rise of large-scale machine learning models, such as GPT, LLaMa, and DALL-E, has revolutionized the development of AI systems but poses challenges for real-world deployment, particularly in edge computing environments with limited resources. This paper presents a comprehensive benchmark for simulating edge computing with multi-modal AI models, focusing on optimizing these complex architectures for the Artificial Intelligence of Things (AIoT). We address key challenges such as model size reduction, computational resource constraints, and federated learning environments. Specifically, we propose methods including model pruning, quantization, and reinforcement learning-based optimization for adaptive offloading to enhance performance while maintaining accuracy. By leveraging techniques such as Vision Transformer pruning and quantization, we demonstrate how to scale down large multimodal networks for efficient deployment on edge devices. Our experiments show significant improvements in computational efficiency and reduced training times, making these models more feasible for real-world AIoT applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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A Novel Approach on Deep Reinforcement Learning for Improved Throughput in Power-Restricted IoT Networks 1

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International Conference on Electrical and Electronics Engineering, ICEEE 2023

作者： Sweety Bakyarani, E. Singh, Navneet Pratap Shekhawat, Jyoti Bhardwaj, Saurabh Chaku, Shweta Singh, Jagendra Department of Computer Science SRM Institute of Science and Technology Kattankulathur India School of Computer Science Engineering and Technology Bennett University Greater Noida India Vivekanand Global University Rajasthan Jaipur India Department of Information Technology Raj Kumar Goel Institute of Technology AKTU Lucknow Ghaziabad India Department of Computer Science Engineering Inderprastha Engineering College AKTU Lucknow Ghaziabad India

ISBN: (数字)9789819986613

ISBN: (纸本)9789819986606

The rapid expansion of the Internet of Things (IoT) has stressed the importance of energy-efficient communication protocols, particularly in networks operating under power constraints. This paper presents a unique approach for managing communication in energy-limited IoT networks using a deep reinforcement learning (DRL)-based communication protocol. By integrating Sparse Code Multiple Access (SCMA), Code Division Multiple Access (CDMA) techniques, and the Combined Experience Replay Deep Deterministic Policy Gradient (CER-DDPG) algorithm, we developed a novel protocol to improve the throughput of power-constrained sensors in an IoT network. Through comprehensive simulations, we compared the proposed protocol’s performance with benchmark systems like traditional DDPG and stochastic algorithms. The results reveal superior energy efficiency and throughput with the proposed protocol, establishing its potential to significantly enhance the performance of energy-constrained IoT networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Disentangling the Problem Space: A Validated Problem Statement for Sustainability Support Systems 19th

Disentangling the Problem Space: A Validated Problem Stateme...

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19th International Conference on Design science Research in Information Systems and Technology (DESRIST) - Design science Research for a Resilient Future

作者： Beermann, Vincent Rieder, Annamina Uebernickel, Falk vom Brocke, Jan Univ Potsdam Hasso Plattner Inst Potsdam Germany Simon Fraser Univ Beedie Sch Business Burnaby BC Canada Univ Munster Munster Germany ERCIS European Res Ctr Informat Syst Munster Germany

ISBN: (纸本)9783031611742;9783031611759

The literature on information systems (IS) has produced empirical evidence that IS can support behavior changes toward sustainability. Leveraging design science research (DSR) methodologies, this paper concentrates on the problem analysis around designing for sustainable behavior, especially by investigating the challenges and potential solutions to resource conservation of energy and water in residential environments. Collaborating with a real estate management firm, we employ the echeloned DSR (eDSR) approach in a field setting, focusing on the problem analysis echelon to refine the problem of encouraging sustainable behaviors among residents. We contribute to the DSR body of knowledge by demonstrating the utility of the eDSR methodology in navigating complex problem spaces, particularly those related to sustainability in IS. We provide a detailed account of our problem-analysis process and offer insights into the role of continuous problem refinement in DSR.

关键词： Design science Research Pro-Environmental Behavior Decision-Making Behavior Change

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A New Membrane Algorithm Based on Quasi-Affine TRansformation Evolution for Optimization Problems 1

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Wang, Xiaopeng Snášel, Václav Mirjalili, Seyedali Chu, Shu-Chuan Shehadeh, Hisham A. Bai, Zhonghai Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Ostrava70800 Czech Republic Centre for Artificial Intelligence Research and Optimisation Torrens University Australia Brisbane4006 Australia College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Faculty of Computer Science and Informatics Amman Arab University Amman11953 Jordan

ISBN: (数字)9789819700684

ISBN: (纸本)9789819700677

This paper develops a new meta-heuristic algorithm, called Membrane Algorithm based on Quasi-Affine TRansformation Evolution (MA-QUATRE). The proposed algorithm combines the principles of QUATRE, the one-level membrane structure, and the rules of membrane systems. The different operations of QUATRE are for each inner elementary membrane and outer skin membrane, and the transformation/communication is like rules in membrane systems. For the effectiveness of MA-QUATRE, it is first evaluated on the CEC2022 benchmark and compared with five QUATRE-related algorithms. Further, the proposed algorithm is used to solve two engineering design problems (tension/compression spring and pressure vessel design) and compared with the original QUATRE and six state-of-the-art algorithms. Finally, experimental results show that the proposed MA-QUATRE is a competitive algorithm for optimization problems. The source codes of this algorithm can be found in https://***/matlabcentral/fileexchange/134372-ma-quatre and https://***/wangxper/***. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Membranes

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On the Design of computer-Aided Translation Teaching 21st

On the Design of Computer-Aided Translation Teaching

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21st International Conference on Web-Based Learning / 7th International Symposium on Emerging Technologies for Education (ICWL/SETE)

作者： Lin, Beibei Zhejiang Univ Technol Coll Foreign Languages Hangzhou Peoples R China

ISBN: (纸本)9783031330223;9783031330230

The current translation teaching turns out to be poor in efficiency. Many students lack practical ability and cannot sufficiently deal with translation tasks in reality. How to motivate their study initiative and improve their translation ability is the question we are interested in. This study tries to make full use of the computer technology and advance the traditional teaching mode with the aid of the Clinknotes online platform, designed for translation teaching. In accordance with the characteristics of translation course, we, taking the Task-Based Language Teaching approach, apply this platform and design the classroom teaching in a new way. Students are well encouraged to participate in the study and give prompt responses to the translation task with several rounds of discussion. It finds that the design of this teaching model can have a positive impact on students' learning efficiency. We hope this study could be enlightening for the future teaching reform.

关键词： Online Teaching Platform Translation Teaching Task-Based Language Teaching (TBLT)

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PSG-Adapter: Controllable Planning Scene Graph for Improving Text-to-Image Diffusion 17th

PSG-Adapter: Controllable Planning Scene Graph for Improvin...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Gao, Yi Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9789819609161

Significant progress in text-to-image generation has been driven by the application of diffusion models, highlighting their crucial role and exceptional impact on this field. However, diffusion models often fall short of comprehending spatial relationships within text. This limitation primarily stems from their challenge in constructing logical spatial relationships, such as distinguishing between foreground and background elements. Additionally, their limited text encoding capacity exacerbates inconsistencies in the generated images derived from textual prompts. In this paper, we introduce the Planning Scene Graph Adapter (PSG-Adapter). Our approach employs Planning Scene Graph (PSG) method to decompose the original text prompt into distinct subprompts containing spatial relationships. By leveraging the proposed Planning Scene Graph ControlNet (PSG-ControlNet), additional spatial information is infused into original text embeddings. By fully exploiting the implicit spatial relationships within the text, our method achieves fine-grained control over the composition of the generated images. This enhancement is particularly notable in scenarios involving the generation of multiple objects and complex spatial relationships. Extensive experiments have been conducted to verify the efficacy of PSG-Adapter in generating spatially coherent images and complex scenes with multiple objects and relationships. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Exploration of computer Vision Systems in the Recognition of Characteristics in Parts in an Industrial Environment 23rd

Exploration of Computer Vision Systems in the Recognition of...

引用

23rd EPIA Conference on Artificial Intelligence, EPIA 2024

作者： Rodrigues, João Ribeiro, Jorge ADiT LAB - Applied Digital Transformatio Laboratory Instituto Politécnico de Viana do Castelo Viana do Castelo Portugal

ISBN: (纸本)9783031734960

With the success of the applicability of Artificial Intelligence and Machine Learning (AI/ML), approaches in the field of computer vision has been highlighted, such as the recognition of objects and their intrinsic details. Within the manufacturing sector, especially in the automotive industry, there has been a motivation for urgent innovations and implementations of computer vision systems to control the assembly of the parts and their visual quality lately, in order to replace old equipment, such as cameras and scanners that have carried out this very limited verification until today, as well as the software license costs. Although there are multiple suppliers of this type of software on the market, it’s important to explore alternatives to reduce this expensive hardware and software license cost that comes with this innovation predicted by the Industry 4.0 global scope. In this sense, using AI/ML approaches for computer vision, in this work, we propose a cheaper method to explore and implement object detection applications in the assembly lines, as well as their particularities and characteristics, calculating distances between components and managing other visual quality elements, built on top of the YOLO architecture, one of the biggest and leading algorithms if the computer vision field. Promising results have been achieved in real scenarios, namely in the detection of the bag ear, plastic and metal clip, tapes and oeticker detection and measurements and in smart area inference simulations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Plastic tapes

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A Typology of Knowledge Creation in Design science Research Projects 19th

A Typology of Knowledge Creation in Design Science Research ...

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19th International Conference on Design science Research in Information Systems and Technology (DESRIST) - Design science Research for a Resilient Future

作者： Chatterjee, Samir Bhattacherjee, Anol Gilb, Tom Claremont Grad Univ Claremont CA 91701 USA Univ S Florida Tampa FL 33620 USA Gilb Com Oslo Norway

ISBN: (纸本)9783031611742;9783031611759

There is considerable debate in IS-DSR community about what constitutes design knowledge and whether they are best represented as design principles or design theories. While designing an IT artifact to solve a problem addresses the "how" question, we agree that the "why" question (why did this work?) is important to answer. This essay attempts to shed light on two fundamental questions in this domain: (1) What are the various ways that knowledge contribution in DSR can be stated? (2) What pathways exists to create and re(use) knowledge in DSR projects? We present a simple 2 x 2 framework that explains with concrete examples four knowledge types - design principles, design attribute postulates, design theories, and good design practices from DSR projects. We further present a dual-use of design knowledge framework that shows pathways and re(use) of knowledge in DSR. We think that this typology is a useful theoretical contribution that can benefit both academics and practitioners conducting DSR projects.

关键词： Design science research knowledge contribution knowledge creation design theories design principles knowledge pathways

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Cross-Modality Complementary Learning for Video-Based Cloth-Changing Person Re-identification 17th

Cross-Modality Complementary Learning for Video-Based Cloth...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Nguyen, Vuong D. Mantini, Pranav Shah, Shishir K. Quantitative Imaging Lab Department of Computer Science University of Houston Houston United States

ISBN: (纸本)9789819608843

Video-based Cloth-Changing Person Re-ID (VCCRe-ID) is a real-world Re-ID problem where individuals are observed in settings with a high likelihood of clothing changes between observations. To tackle this problem, capturing cloth-invariant modalities remains more effective than texture-based approaches. However, previous works extracted these modalities separately and directly leveraged the learned features for Re-ID, which is not effective since viewpoint changes and occlusion cause severe ambiguity in these modalities. To address this limitation, we propose a dual-branch framework that couples cloth-invariant modalities (i.e. shape and gait) with appearance by novelly exploiting the complementary relationship across them. In this work, we design a texture branch that enables body shape to complement the ambiguity in appearance caused by illumination variations or occlusions. Then texture and gait features are mutually learned at multiple levels, which helps to exchange beneficial information across branches for more discriminative person representations. We build a large-scale video-based cloth-changing dataset that contains the most cloth variations and is the first benchmark that mimics the real-world similar-clothing scenario. Extensive experiments show that our proposed framework outperforms state-of-the-art methods by a large margin. Code and dataset will be available at https://***/dustin-nguyen-qil/CCL-VCCReID. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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A Novel Approximation Algorithm for Max-Covering Circle Problem 16th

A Novel Approximation Algorithm for Max-Covering Circle Pro...

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16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023

作者： Zhang, Kaiqi Zhang, Siyuan Gao, Jirun Wang, Hongzhi Gao, Hong Li, Jianzhong School of Computer Science and Technology Harbin Institute of Technology Harbin China School of Computer Science and Technology Zhejiang Normal University Jinhua China Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9783031496103

We study the efficient approximation algorithm for max-covering circle problem. Given a set of weighted points in the plane and a circle with specified size, max-covering circle problem is to find the proper place where the center of the circle is located so that the total weight of the points covered by the circle is maximized. Our core approach is to approximate the circle with a symmetrical rectilinear polygon (SRP). We first present a method to construct the circumscribed SRP of a given circle and disclose their area relationship. Then, we convert max-covering SRP problem to SRP intersection problem, which can be efficiently solved with simple partition and modification based on the existing method. Finally, the optimal solution returned from max-covering SRP problem can be used to produce an approximate answer to max-covering circle problem. We prove that for most of the inputs, our algorithm can give a (1 - Ε) approximation to the optimal solution, which only needs O(nΕ-1logn+nΕ-1log(1Ε)) time for unit points and o(nΕ-2logn) time for weighted points. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Approximation algorithms

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