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共 31068 条记录，以下是4921-4930 订阅

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Return-of-Interest Conscious Truth Inference for Crowdsourcing Queries

Return-of-Interest Conscious Truth Inference for Crowdsourci...

引用

26th International Conference on Technologies and Applications of Artificial Intelligence, TAAI 2021

作者： Leung, Lok-Him Yang, Po-An Chuang, Kun-Ta National Cheng Kung University Dept. of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781665408257

In the big data era, the flourishing development of Internet services brings a lot of user generated data, in which most new information cannot be systematically retrieved by current knowledge bases. For example, a dramatic number of new hashtags appear in the social media every day, resulting in much unknown but valuable knowledge that requires reliable category/attribute labeling strategies. The crowdsourcing platform provides an effective tool to leverage opinions from the Internet crowd. In this paper, we propose incorporating varied task importance, called Return of Interest (RoI), into resource allocation in crowdsourcing. The awareness of RoI is important in the business sense, but it introduces new challenges. In this paper, we propose a two-phase framework, called Macro-Assignment and Micro-Optimization (MAMO), to simultaneously consider the issue of budget allocation and the chance of iteratively obtaining RoI. With the fixed budget, we prove that worker allocation to diverse pools for the best expectation of RoI in return is a NPhard challenge. We propose a Dynamic-Programming strategy to resolve the issue effectively. As shown in our experimental results, we demonstrate that the DP-based strategy can significantly outperform the baseline greedy approaches, also indicating its feasibility to be deployed as the standard component for budget allocation in crowdsourcing. © 2021 IEEE.

关键词： Budget control

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Appearance-guided particle filtering for articulated hand tracking

Appearance-guided particle filtering for articulated hand tr...

引用

2005 IEEE computer Society Conference on computer Vision and Pattern Recognition, CVPR 2005

作者： Chang, Wen-Yan Chen, Chu-Song Hung, Yi-Ping Institute of Information Science Academia Sinica Taipei Taiwan Dept. of Computer Science and Information Engineering National Taiwan University Taiwan

ISBN: (纸本)769523722

We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance information. A probability propagation model is derived from a Bayesian formulation for this framework, and a sequential Monte Carlo method is introduced for its realization. We apply the proposed method to articulated hand tracking, and show that it performs better than methods that only use either sequential motion transition information or only use appearance information. © 2005 IEEE.

关键词： computer vision

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Group working differential evolution 9

Group working differential evolution

引用

9th IEEE Global Conference on Consumer Electronics, GCCE 2020

作者： Niwa, Takatoshi Ihara, Koya Kato, Shohei Nagoya Institute of Technology Gokiso-cho Showa-ku Dept. of Computer Science and Engineering Nagoya466-8555 Japan Nagoya Institute of Technology and Frontier Research Institute for Information Science Gokiso-cho Showa-ku Dept. of Computer Science and Engineering Nagoya466-8555 Japan

ISBN: (纸本)9781728198026

Cooperative Coevolution (CC) is a method of improving the efficiency of evolutionary computation. Decision variables are divided into several species and the optimization is performed in each species. Search does not work in CC without properly dividing decision variables. In this paper, we combine the evaluation method of CC that can be searched without properly dividing the decision variables with Differential Evolution. The effectiveness of the search performance was evaluated using four benchmark functions, and the effectiveness was confirmed in the functions that have a dependency between variables. © 2020 IEEE.

关键词： Evolutionary algorithms

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An Advanced MIMO Multicarrier Framework for NTN-Based 5G Broadcast/Multicast Transmissions 11

An Advanced MIMO Multicarrier Framework for NTN-Based 5G Bro...

引用

11th IEEE International Workshop on Metrology for AeroSpace, MetroAeroSpace 2024

作者： Rahman, Talha Faizur Marojevic, Vuk Sacchi, Claudio Mississippi State University Dept. of Electrical and Computer Engineering Mississippi StateMS United States University of Trento Dept. of Information Engineering and Computer Science Trento Italy The University of New Mexico Dept. of Electrical Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350385045

Satellites are teaming up with 5G, forming a non-terrestrial network (NTN), to support broadband applications over wide coverage areas. However, low latency and high reliability are the challenges in NTN which is addressed through the use of low-earth orbit (LEO) satellites. High transmission efficiency can be accomplished by employing multiple-input multiple-output (MIMO) antenna systems and multicarrier wave-forms. Conventional multicarrier techniques, such as Orthogonal Frequency Division Multiplexing (OFDM) and its variants, are sensitive to the nonlinear distortion of high power amplifiers (HPAs) and high Doppler environments. Therefore, we consider Constant Envelope OFDM (CE-OFDM) assisted with Space-Time Shift Keying (STSK) and Low-Density Parity Check (LDPC) encoding for 5G broadcast/multicast systems based on LEO satellites working in the L-band. We propose a low complexity receiver based on A Posteriori Probability (APP) STSK decoding integrated with LDPC decoding, in which we derive the APP of LDPC coded bits for the STSK-CE-OFDM transmission. We analyze the computational complexity of the proposed receiver scheme and conclude that it is effective in counteracting HPA nonlinearity and high Doppler effects inherent to LEO satellites. Numerical results show that the proposed framework outper-forms conventional multicarrier techniques with a gain as high as 16 dB in the presence of amplifier nonlinearity. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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Cooperative routing approach for ISP-provided content delivery service using hierarchical DHT

Cooperative routing approach for ISP-provided content delive...

引用

IEEE International Conference on High Performance Computing and Communication

作者： Jung, Kyounghee Kim, Dohyun Lee, Younghee Division of Media Technology Media Business Center KT Corporation Korea Republic of Dept. of Information and Communication Engineering KAIST Korea Republic of Dept. of Computer Science KAIST Korea Republic of

ISBN: (纸本)9780769542140

This paper suggests ISP-provided content delivery service that provides fine-grained locality and exploits network status in content routing to overcome the dilemma from current content delivery technology like P2P. Hierarchical DHT provides an efficient and scalable distributed data service architecture and it is able to achieve high level of locality over ISP network which has a hierarchical topology in general. However, simple implementation of it into ISP network imposes several issues: long query length, overloading, and the ignorance of network status in routing which is one of strengths of ISP-provided service. In order to resolve the aforementioned issues, this paper introduces network domain heuristic based merging and dynamic cost-based cooperative routing that exploits service load and network cost together. According to simulation based evaluation, our proposed approach achieves around 40% shorter latency in both delivery and query. Furthermore, it can alleviate overloading and content delivery through contested path efficiently. © 2010 IEEE.

关键词： Internet service providers

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Diffusion inverse square-root recursive least square-based algorithm with adaptive network 18

Diffusion inverse square-root recursive least square-based a...

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18th International Conference on Electrical engineering/Electronics, computer, Telecommunications and information technology, ECTI-CON 2021

作者： Sitjongsataporn, Suchada Prongnuch, Sethakarn Wiangtong, Theerayod Faculty of Engineering and Technology Dept. of Electronic Engineering Bangkok Thailand Suan Sunandha Rajabhat University Faculty of Industrial Technology Dept. of Computer Engineering Bangkok Thailand King Mongkut's Institute of Technology Ladkrabang Faculty of Engineering Dept. of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9780738111278

In this paper, a Combine-Then-Adapt diffusion strategy on adaptive recursive least square algorithm (RLS) is proposed with adaptive network. We apply the inverse autocorrelation matrix based on the QR-decomposition method in order to reduce the complexity. The Combine-Then-Adapt diffusion strategy is modified on the inverse square-root recursive least square (iQR-RLS) algorithm including with the combination and adaptation steps. By applying an idea of diffusion strategy and mixed cost function, we derive a diffused version of an inverse square-root recursive least square algorithm, named as DiQR-RLS. Experimental results demonstrate that the proposed DiQR-RLS can achieve clearly the better performance than the conventional recursive least square algorithm. © 2021 IEEE.

关键词： Cost functions

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Unmasking the AI Hand: A Machine Learning Approach to Deciphering Authorship 3

Unmasking the AI Hand: A Machine Learning Approach to Deciph...

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3rd International Conference for Innovation in technology, INOCON 2024

作者： Bhandarkar, Abhay Mushtaq Ahmed, D.M. Vishwachetan, D. Mushtaq, Arfaat Kadam, Dhrithi Saxena, Salaj Ramaiah Institute of Technology Dept. of Computer Science and Engg Bangalore54 India Ramaiah Institute of Technology Dept. of Information Science and Engg Bangalore54 India

ISBN: (纸本)9798350381931

In an era of explosive data growth, accurate text analysis tools are paramount. The surge of AI-generated texts presents a pressing challenge: discerning human-written content from AI-generated content. This affects text analysis accuracy, necessitating innovative solutions. We introduce an AI-driven model within the Model-View-Controller (MVC) architecture, categorising text as AI-generated or human-authored. Leveraging supervised learning, the model uses Count Vectorizers and Multinomial Naive Bayes algorithm for training and classification. The proposed model shows a good accuracy of 86.2%. This, with enhanced precision and F1 scores, underscores efficacy in classifying text origins. Beyond its immediate contributions, our model promises to reshape content authenticity verification, from AI-generated social media posts to verifying news sources. The model offers future directions, advancing AI-generated content detection. As AI-generated content evolves, our approach ensures credibility and reliability in text analysis within the MVC framework, addressing the critical need to navigate the AI-generated content landscape. © 2024 IEEE.

关键词： Reliability analysis

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Connective Reconstruction-Based Novelty Detection 31

Connective Reconstruction-Based Novelty Detection

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31st International Conference on Electrical engineering, ICEE 2023

作者： Hashemi, Seyyed Morteza Aliniya, Parvaneh Razzaghi, Parvin Institute for Advanced Studies in Basic Sciences Dept. Computer Science and Information Technology Zanjan Iran University of Nevada Dept. Computer Science RenoNV United States

ISBN: (纸本)9798350312560

Detection of out-of-distribution samples is one of the critical tasks for real-world applications of computer vision. The advancement of deep learning has enabled us to analyze real-world data which contain unexplained samples, accentuating the need to detect out-of-distribution instances more than before. GAN-based approaches have been widely used to address this problem due to their ability to perform distribution fitting;however, they are accompanied by training instability and mode collapse. We propose a simple yet efficient reconstruction-based method that avoids adding complexities to compensate for the limitations of GAN models while outperforming them. Unlike previous reconstruction-based works that only utilize reconstruction error or generated samples, our proposed method simultaneously incorporates both of them in the detection task. Our model, which we call 'Connective Novelty Detection' has two subnetworks, an autoencoder, and a binary classifier. The autoencoder learns the representation of the positive class by reconstructing them. Then, the model creates negative and connected positive examples using real and generated samples. Negative instances are generated by manipulating the real data, so their distribution is close to the positive class to achieve a more accurate boundary for the classifier. To boost the robustness of the detection of reconstruction error, connected positive samples are created by combining the real and generated samples. Finally, the binary classifier is trained using connected positive and negative examples. We demonstrate a considerable improvement in novelty detection over state-of-the-art methods on MNIST and Caltech-256 datasets. © 2023 IEEE.

关键词： computer vision

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Smart Shopping Cart Using Radio Frequency Identification

Smart Shopping Cart Using Radio Frequency Identification

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2024 IEEE International Students' Conference on Electrical, Electronics and computer Science, SCEECS 2024

作者： Kesava, Gudipati Rishi Reddy, Vanukuri Karthik Trivikram, Sadineni Santhi Sri, K. Vignan's Foundation for Science Technology & Research Deemed to Be University Dept. Information Technology & Computer Applications Guntur India

ISBN: (纸本)9798350348460

The "Smart Shopping Cart Using Radio Frequency Identification"project revolutionizes the shopping experience through RFID technology, offering real-time cost updates to shoppers. This innovative system incorporates RFID readers, a microcontroller for instant cost computations, and an LCD screen for displaying the total expense. By tackling common issues associated with traditional shopping carts, like prolonged checkout procedures and the absence of live cost monitoring, our project significantly enhances the efficiency and convenience of shopping. Shoppers can now enjoy a seamless experience as the RFID technology effortlessly scans tagged products, allowing the microcontroller to promptly calculate the overall cost, which is then displayed on the LCD screen. This breakthrough not only streamlines the shopping process but also eliminates the need for manual price entries, reducing errors and enhancing overall customer satisfaction. The successful integration of these technologies marks a promising step towards the future of retail, where smart shopping carts pave the way for quicker, more accurate, and enjoyable shopping ventures. © 2024 IEEE.

关键词： Efficiency and Convenience Radio Frequency Identification (RFID) Real-time Cost Updates RFID technology Integration Seamless Shopping Experience Smart Shopping Cart

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Independent component analysis of quaternion Gaussian vectors

Independent component analysis of quaternion Gaussian vector...

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IEEE Sensor Array and Multichannel Signal Processing Workshop

作者： Via, Javier Vielva, Luis Santamaria, Ignacio Palomar, Daniel P. Dept. of Communications Engineering University of Cantabria Spain Dept. of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

ISBN: (纸本)9781424489770

This paper addresses the independent component analysis (ICA) of quaternion Gaussian vectors. Firstly, we define the properness profile of a quaternion random variable, which can be seen as the quaternion analogue of the circularity coefficients of complex vectors. The properness profile is a three-dimensional pure quaternion vector, which does not only measure the improperness degree of the quaternion random variable, but also provides the improperness distribution. Secondly, we prove that the quaternion ICA model can be identified up to the trivial scale and permutation ambiguities, and a residual quaternion mixture among the sources with rotationally equivalent properness profiles, i.e., properness profiles related by a quaternion rotation. Finally, the main results of the paper are illustrated by means of some numerical examples. © 2010 IEEE.

关键词： Random variables

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