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检索条件"机构=Computer Eng. and Computer Science Department"

共 9305 条记录，以下是1-10 订阅

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Evaluation of Mapping computer Vision Segmentation from Reality Capture to Schedule Activities for Construction Monitoring in the Absence of Detailed BIM 41

Evaluation of Mapping Computer Vision Segmentation from Real...

引用

41st International Symposium on Automation and Robotics in Construction, ISARC 2024

作者： Núñez-Morales, Juan D. Jung, Yoonhwa Golparvar-Fard, Mani Department of Civil and Environmental Eng. and Computer Science United States Department of Civil and Environmental Eng. Computer Science and Technology Entrepreneurship United States University of Illinois at Urbana-Champaign United States

ISBN: (纸本)9780645832211

Over the past few years, research has focused on leveraging computer vision in construction progress monitoring, particularly in comparing construction photologs to Building Information Modeling (BIM), with or without schedule data. The practical application of these techniques and a large number of startups that have brought hyper AI and human-in-the-loop services around progress monitoring have revealed several gaps: 1) Current BIM-driven projects do not have model disciplines at the right level of maturity and Level of Development;2) definitions of states of work-in-progress that are detectable from images are not formalized;3) poor schedule quality and lack of frequent progress update challeng.s the incorporation of detailed 4D BIM for progress tracking. Such gaps are addressed in this work by exploring the requirements for mapping modern computer vision techniques for object segmentation with construction schedule activities to automate progress monitoring applications using computer vision without BIM as a baseline. The approach utilizes reality mapping practices to offer time machines for construction progress, organizing photologs over space and time. Additionally, this work shows how Large Language Models can structure schedule activity descriptions around , focusing on how vision and language models can be trained separately with limited annotated data. ASTM Uniformat classification is utilized to map triangulated object segments from images to color-coded 3D point clouds aligned with schedule activities without the need for image and language feature alignments. Exemplary results on tied new transformer-based models with few-shot learning are shown, and the requirements for full-scale implementation are discussed. © 2024 ISARC. All Rights Reserved.

关键词： computer vision

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Optimizing Resource Allocation for Device to Device Communication in Cellular Networks 5

Optimizing Resource Allocation for Device to Device Communic...

引用

5th IEEE International Conference on Recent Trends in computer science and Technology, ICRTCST 2024

作者： Salim, Abu Tiwari, Rajesh Kumar Siddiqui, Shams Tabrez Tahir, Ali Kamal, Mohammad Shahid Sarfaraz, Mohammad Jazan University College of Engineering and Computer Science Department of Computer Science Jazan Saudi Arabia RVS College of Eng. & Tech Department of Computer Science and Engineering Jamshedpur Jharkhand India

ISBN: (纸本)9798350351378

Device-to-device communication is a noteworthy technology that can improve the efficiency and capacity of cellular networks. Efficient resource allocation is crucial in a cellular network that supports both device-to-device communication and traditional cellular users. To minimize interference and optimize the overall performance of the network, this allocation is necessary. The current study introduces a new framework aimed at improving the spectrum efficiency and quality of service in device-to-device interactions. The framework utilizes interference management techniques to achieve these enhancements. The research conducted encompasses a comprehensive examination of the subject matter, incorporating theoretical analysis, simulation results, and practical implications. This approach has been employed to effectively showcase the advantages and benefits associated with the proposed methodology. © 2024 IEEE.

关键词： Resource allocation

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Color and Grayscale Pencil Image Translation Into Realistic Images Using Generative Adversarial Networks 5

Color and Grayscale Pencil Image Translation Into Realistic ...

引用

5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Yeshani, R.K.B. Chiththranjan, Charith University of Moratuwa Dept. of Computer Science and Eng. Sri Lanka

ISBN: (纸本)9798331530983

This work presents an innovative approach to image-to-image translation, focusing on converting colour pencil images, grayscale pencil images, and grayscale images into RGB images using the Pix2Pix GAN. Building upon the established Pix2Pix framework, which utilizes a U-Net based architecture with skip connections for the generator and a Patch-GAN discriminator. This aims to refine the translation process, addressing the images' intricate details and colour dynamics. Empirical results demonstrate that this generator architecture significantly outper- forms the U-Net architecture in producing more vivid, detailed and accurate RGB images. By leveraging this method, the study not only contributes to the body of knowledge in neural network applications for artistic image translation but also opens new avenues for further researches in image translations. This work underscores the potential of targeted architectural modifications within GAN frameworks to achieve image translation outcomes, thereby setting a precedent for future explorations in the field. © 2025 IEEE.

关键词： Deep learning

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Location Based Data-Centric Forwarding for Mobile Ad-Hoc Networks 26

Location Based Data-Centric Forwarding for Mobile Ad-Hoc Net...

引用

26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Nguyen, Hieu Ra, Ilkyeun University of Colorado Denver Department of Computer Science and Eng. DenverCO United States

ISBN: (纸本)9791188428120

With the ever-increasing usage and deployment of mobile devices, mobile ad-hoc networks have become more and more prevalent in replacing centralized networks. However, high mobility of nodes can lead to challeng.ng performance issues, such as high packet loss, frequent path failures causing high route-reinitiating overheads, and significant data retrieval delay. Named Data Networking (NDN) offers an alternative solution to these problems. But, existing approaches still have many issues and can be further improved. This paper proposes a novel location-based approach that aims to address existing challeng.s of using NDN in mobile ad hoc networks and improve the performance of existing works. The simulation results presented in the paper prove that our approach is very much feasible. © 2024 Global IT Research Institute - GIRI.

关键词： Mobile ad hoc networks

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Exploring Various Data Security Methods for Enhancing Security in Cloud Computing 2

Exploring Various Data Security Methods for Enhancing Securi...

引用

2nd International Conference on Advanced Computing and Communication Technologies, ICACCTech 2024

作者： Rubi Rani, Sunita Saroha, Vinod Kr. Beniwal, Sonal Bhagat Phool Singh Mahila Vishwavidyalaya Department of Computer Science Eng. & IT Sonipat India

ISBN: (纸本)9798331519056

Today in the information technology (IT) field the continued advancement in technology cloud computing plays a crucial role in sharing, storing and retrieving data from anywhere anytime. In the present day, the large number of devices connected through the internet creates big amounts of data and raises security and privacy issues. This paper target is a comprehensive review of various existing data security techniques such as cryptography, steganography, homomorphic encryption, machine learning, deep learning, Deoxyribonucleic Acid (DNA) cryptography, quantum cryptography and blockchain that are used in cloud environments for safe transmission and storage of data. The paper identifies the key points of each technique and shows the compression among them for a better understanding the usability of each technique. It provides the knowledge of which technique is suitable when and how and describes the current status of data security technology. The earlier work regarding different security methods and their identification has been enveloped together in this paper for presenting detailed insight. © 2024 IEEE.

关键词： Cloud security

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MODEL-DRIVEN eng.NEERING FOR HIGH-PERFORMANCE PARALLEL DISCRETE EVENT SIMULATIONS ON HETEROGENEOUS ARCHITECTURES

MODEL-DRIVEN ENGINEERING FOR HIGH-PERFORMANCE PARALLEL DISCR...

引用

2024 Winter Simulation Conference, WSC 2024

作者： Marotta, Romolo Pellegrini, Alessandro Dept. of Civil Eng. and Computer Science Eng. Tor Vergata University of Rome Rome Italy

ISBN: (纸本)9798331534202

Modern high-performance, large-scale simulations require significant computational power, memory, and storage, making heterogeneous architectures an attractive option. The presence of accelerators in heterogeneous architectures makes model development hard. Domain-specific languages (DSLs) have successfully simplified model development, but designing a DSL to target heterogeneous architectures can be burdensome. Model-driven eng.neering (MDE) can simplify the development of DSLs targeting heterogeneous architectures. In this paper, we focus on MDE and propose a model-driven approach targeting Parallel Discrete Event Simulations on heterogeneous architectures. We exercise our MDE-generated models using a state-of-the-art runtime environment for heterogeneous architectures. © 2024 IEEE.

关键词： Parallel architectures

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Multimodal Emotion Recognition Exploiting Audio, Video and Textual Features with Crossmodal Attention

Multimodal Emotion Recognition Exploiting Audio, Video and T...

引用

2024 IEEE International Women in eng.neering (WIE) Conference on Electrical and computer eng.neering, WIECON-ECE 2024

作者： Das, Avishek Sarma, Moumita Sen Hoque, Mohammed Moshiul Chittagong University of Eng. & Technology Dept. of Computer Science and Eng Chattogram Bangladesh

ISBN: (纸本)9798331535476

Multimodal emotion recognition (MER) aims to identify and understand human emotions by integrating data from diverse sources such as speech signals, facial expressions, and textual content. This process requires addressing the complexities of merging varied data modalities, each of which presents unique challeng.s, including noise, variability, and inconsistencies in how emotional cues are expressed and perceived. This paper proposes a unique approach to MER by utilizing three complementary modalities-audio, video, and text-to classify emotions into distinct categories: anger, fear, joy, and sadness. The paper presents pairwise crossmodal attention to enhance the integration of unimodal features, which are then combined and processed through an artificial n eural n etwork (ANN) for classification. A key contribution of this work is the creation of the MAViT (Multimodal Audio Video Text) dataset, comprising 1,002 multimodal samples. The experimental results highlight the superior performance of the multimodal approach, achieving an F1 score of 0.62. Unimodal results were also analyzed in detail, further demonstrating the advantages of integrating data from multiple modalities to provide a more accurate and nuanced understanding of emotions. © 2024 IEEE.

关键词： Emotion Recognition

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Detecting Fake Reviews on E-commerce Platforms Using Machine Learning 3

Detecting Fake Reviews on E-commerce Platforms Using Machine...

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Vashist, Ansh Keswani, Arul Pareek, Varda Jain, Tarun Manipal University Jaipur Dept. of Computer Science & Eng. India

ISBN: (纸本)9798350354348

Currently, reviews on different e-commerce websites are fake and mostly posted by the company itself to increase the reach or sale of the product itself. These reviews are mostly generated by different bots or written manually. This study provides a novel framework that combines machine learning (ML) and natural language processing (NLP) methods to identify fraudulent reviews on e-commerce platforms. The system is subjected to extensive data preparation and feature extraction, utilising cutting-edge natural language processing techniques to identify subtle linguistic patterns and emotions. By utilising supervised and unsupervised machine learning methods, together with ensemble learning for enhanced precision, the model successfully differentiates between authentic and fraudulent reviews. Experiments conducted on real-world datasets show that the system performs robustly, avoiding false positives, while maintaining high detection rates. This study makes a substantial contribution to improving the integrity of e-commerce platforms by offering workable solutions to prevent fraud and protect customer confidence. © 2024 IEEE.

关键词： Adversarial machine learning

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Concept Drift Complexity for Assessing Sampling-Induced Concept Drift in Class-Imbalanced Data Streams 12

Concept Drift Complexity for Assessing Sampling-Induced Conc...

引用

12th IEEE International Conference on Intelligent Systems, IS 2024

作者： Hajmohammed, Mustafa Chountas, Panagiotis Chaussalet, Thierry J. School of Computer Science & Eng. University of Westminster London United Kingdom

ISBN: (纸本)9798350350982

Resampling data is an eng.neering technique that has an impact on instances where the underlying data distribution and proportions of instances and classes change as a result. Applying any resampling technique may influence the occurrence of certain phenomena such as concept drift, class imbalance, and anomalies. Such influence may produce, exaggerate or eliminate the presence of these phenomena, whether they are viewed as a problem or as a characteristic of the data. Resampling, such as over- or under-sampling, introduces new challeng.s as well as resolving others. One of the challeng.s of resampling is its impact on concept drift in a data stream. This paper looks at concept drift produced as a result of data resampling, its nature and how to use its complexity as an indicator of performance. Additionally it examines the nature of concept drifts as a result of applying over- and under-sampling techniques and the various different concept drifts produced as a result of these two techniques. Even though concept drift, class imbalance, and resampling techniques have been studied and researched extensively, sampling-induced concept drift itself as a separate phenomenon has been under- researched. This phenomenon has a certain complexity and can have an impact on the model, which can be measured using concept drift complexity especially when using the value of complexity as a baseline for the overall complexity of drift in a dataset. © 2024 IEEE.

关键词： concept drift concept drift complexity data streams sampling techniques sampling-induced concept drift

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Blockchain-Driven Decentralized Healthcare Data Management with IPFS and Elasticsearch

Blockchain-Driven Decentralized Healthcare Data Management w...

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2024 International Conference on computer, Electronics, Electrical eng.neering and their Applications, IC2E3 2024

作者： Mittal, Kratika Kumar, Rajeev Chauhan, Naveen NIT Hamirpur Dept. of Computer Science & Eng. Hamirpur India

ISBN: (纸本)9798350388534

In response to the pressing challeng.s of security, transparency, and interoperability in healthcare data manage-ment, the proposed model emerges as a pioneering solution. This paper introduces a decentralized ecosystem, powered by blockchain, IPFS, and Elasticsearch, aimed at transforming the conventional healthcare data paradigm. Traditional systems often struggle with security concerns and lack transparency in data transactions. The proposed system addresses this gap by employing a permissioned blockchain, ensuring tamper-proof patient records. Leveraging IPFS for decentralized storage and Elasticsearch for real-time data retrieval, the platform offers a resilient and efficient solution. The significance of the proposed system lies in its user-centric design, enabling patients to manage their data securely and providing healthcare providers with swift, real-time access to critical information. This research highlights the project's novel approach, emphasizing enhanced security, transparent data transactions, and improved accessibility. The proposed system acts as a pioneer in rethinking healthcare data management, introducing a solution that harmoniously integrates with the continuously evolving demands of the digital healthcare landscape. As we navigate the complexities of modern healthcare, the proposed system heralds a new era, introducing innovative methodologies that elevate the standards of security, trans-parency, and interoperability in healthcare data management. © 2024 IEEE.

关键词： Electronic health record

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