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IEEE International Conference on Multimedia and Expo (ICME 2007)

作者： Kim, Jong-Ho Kim, Byung-Gyu Cho, Chang-Sik Real-time Multimedia Research Division Electronics and Telecommunications Research Institute Computer Software and Engineering Dept. University of Science and Technology

ISBN: (纸本)9781424410163

Block motion estimation with full search is computationally complex. To reduce this complexity, different methods have been proposed, including partial distortion, which can reduce the computational complexity with no loss of image quality. We propose a distortion-based partial distortion search (DPDS) based on the magnitude of distortion and adaptive update of the matching order. We calculate absolute differences for all pixels in the predicted block point. Pixels are then sorted by the amount of distortion in a descending order for the matching process, which produces a scanning map. The sum of the absolute differences (SAD) of other candidate positions is then computed from this matching order. We also use an update of the scanning map by checking the increase in the number of absolute differences for the SAD value. The proposed DPDS algorithm improves the computational efficiency, compared with the original PDS scheme, because the accumulated value of the absolute pixel differences can rapidly reach the current minimum SAD value. The proposed algorithm is 4-13 times faster than the full search method with the same visual quality.

关键词： Pixels

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A blockchain for media: Survey 18

A blockchain for media: Survey

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18th International Conference on Electronics, Information, and Communication, ICEIC 2019

作者： Cho, Sunghyun Jeong, Chiyoung Electrical and Computer Engineering Division of Software UC San Diego Hanyang University Ansan Korea Republic of Computer Science and Engineering Hanyang University Ansan Korea Republic of

ISBN: (纸本)9788995004449

As the Internet has developed, media distribution services have spread. However, these distribution services have many problems. The blockchain technology can solve these problems. In this paper, this blockchain is defined as media blockchain and is classified into two categories. One is content security that means securing content using blockchain. The other is content right information that means tracing and managing right information using blockchain. We introduce and analyze the media blockchain. © 2019 Institute of Electronics and Information Engineers (IEIE).

关键词： Blockchain

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Machine learning models for automatic labeling: A systematic literature review 15

Machine learning models for automatic labeling: A systematic...

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15th International Conference on software Technologies, ICSOFT 2020

作者： Fredriksson, Teodor Bosch, Jan Olsson, Helena Holmstrm Department of Computer Science and Engineering Division of Software Engineering Chalmers University of Technology Gothenburg Sweden Department of Computer Science and Media Technology Malm University Malm Sweden

ISBN: (纸本)9789897584435

Automatic labeling is a type of classification problem. Classification has been studied with the help of statistical methods for a long time. With the explosion of new better computer processing units (CPUs) and graphical processing units (GPUs) the interest in machine learning has grown exponentially and we can use both statistical learning algorithms as well as deep neural networks (DNNs) to solve the classification tasks. Classification is a supervised machine learning problem and there exists a large amount of methodology for performing such task. However, it is very rare in industrial applications that data is fully labeled which is why we need good methodology to obtain error-free labels. The purpose of this paper is to examine the current literature on how to perform labeling using ML, we will compare these models in terms of popularity and on what datatypes they are used on. We performed a systematic literature review of empirical studies for machine learning for labeling. We identified 43 primary studies relevant to our search. From this we were able to determine the most common machine learning models for labeling. Lack of unlabeled instances is a major problem for industry as supervised learning is the most widely used. Obtaining labels is costly in terms of labor and financial costs. Based on our findings in this review we present alternate ways for labeling data for use in supervised learning tasks. Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： Program processors

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An adaptive feedback system for the improvement of learners

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Scientific Reports 2025年第1期15卷 1-13页

作者： Qadir, Hafiz Muhammad Khan, Rafaqat Alam Rasool, Mudassar Sohaib, Muhammad Shah, Mohd Asif Hasan, Md Junayed Department of Software Engineering Lahore Garrison University Lahore 54810 Pakistan Cantonment Institute of Management and Lands Administration Lahore 54800 Pakistan School of Computer Science and Technology Zhejiang Normal University Jinhua 321004 China Department of Economics Bakhtar University Kart-e-Char Kabul 1001 Afghanistan Dataxense Aberdeen AB11 5RG United Kingdom Division of Research and Development Lovely Professional University 144001 Punjab Phagwara India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University 140401 Punjab Rajpura India

Teachers who are aware of their students’ strengths and weakness can tailor their teaching methodologies to meet the challenging students efficiently for better results. This helps them to identify any potential learning challenges at an early stage leading to improved academic performance and success ratio. This also fosters a learning environment where students feel motivated and valued to excel in their respective fields. This study offers a robust adaptive feedback system tailored for Learning Management System leveraging instance level explorations, helping teachers to find the specific instance affecting the learner’s learning outcome. The proposed system can also be utilized by the institutions where the outcome-based education system has been adopted. The study includes Stacking, Capsule Network, SVM, Random Forest, Decision Tree, and KNN for experiments. Stacking achieved the highest accuracy of 76.70% while SVM demonstrated the highest precision of 0.78 showing the effectiveness of ensemble learning techniques. The primary objective of this endeavor is to elevate automated assessment to provide precise and meaningful feedback, enhancing the educational experience for tertiary students through the integration of technology and pedagogical concepts. The learning feedback has been made available via a user-friendly webserver at: https://***/. © The Author(s) 2025.

关键词： Instance level explorations Learning analytics LMS Machine learning Outcome-based education Tertiary education

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Endurable SSD-Based Read Cache for Improving the Performance of Selective Restore from Deduplication Systems

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Journal of computer Science & Technology 2018年第1期33卷 58-78页

作者： Jian Liu Yun-Peng Chai Xiao Qin Yao-Hong Liu Division of Computer Science and Engineering Louisiana State University Baton Rouge LA 70803 U.S.A. Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education of China Beijing 100872 China School of Information Renmin University of China Beijing 100872 China Shelby Center for Engineering Technology Department of Computer Science and Software Engineering Samuel Ginn College of Engineering Auburn University Auburn AL 368~9-53~7 U.S.A.

Deduplication has been commonly used in both enterprise storage systems and cloud storage. To overcome the performance challenge for the selective restore operations of deduplication systems, solid-state-drive-based （i.e., SSD-based） re^d cache cm, be deployed for speeding up by caching popular restore contents dynamically. Unfortunately, frequent data updates induced by classical cache schemes （e.g., LRU and LFU） significantly shorten SSDs＇ lifetime while slowing down I/O processes in SSDs. To address this problem, we propose a new solution -- LOP-Cache to greatly improve tile write durability of SSDs as well as I/O performance by enlarging the proportion of long-term popular （LOP） data among data written into SSD-based cache. LOP-Cache keeps LOP data in the SSD cache for a long time period to decrease the number of cache replacements. Furthermore, it prevents unpopular or unnecessary data in deduplication containers from being written into the SSD cache. We implemented LOP-Cache in a prototype deduplication system to evaluate its pertbrmance. Our experimental results indicate that LOP-Cache shortens the latency of selective restore by an average of 37.3% at the cost of a small SSD-based cache with only 5.56% capacity of the deduplicated data. Importantly, LOP-Cache improves SSDs＇ lifetime by a factor of 9.77. The evidence shows that LOP-Cache offers a cost-efficient SSD-based read cache solution to boost performance of selective restore for deduplication systems.

关键词： data deduplication solid state drive （SSD） flash cache endurance

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Volume Visualization of Payoff Regions for Derivatives Risk Management 2

Volume Visualization of Payoff Regions for Derivatives Risk ...

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2nd IEEE TCVG / Eurographics International Workshop on Volume Graphics, VG 2001

作者： Fei, Tan Toh Prakash, Edmond Cyril Centre For Graphics And Imaging Technology Division Of Software System School Of Computer Engineering Nanyang Technological University 639798 Singapore

ISBN: (纸本)321183737X

Volume visualization of derivatives helps us discover risks, which hitherto have been elusive with traditional surface plots. In this paper, we would like to address the volatility visualization issue, which is one of the criti- cal components in Option pricing, by incorporating volume visualization for better risk management. By enabling the visualization of volatility changes in risk profiling, combining with another two Option's value de- terminants (i.e. the underlying asset spot price and days to maturity), a much better understanding about the risk involved in a portfolio can be achieved, particularly when the fluctuation of the asset is highly uncertain. © VG 2001. All rights reserved.

关键词： Risk management

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Interference cancellation in RIS-assisted FD relay transmission 14

Interference cancellation in RIS-assisted FD relay transmiss...

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14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Kim, Donghyeon Choi, Wooyeol Chun, Chanjun Kim, Yohan Kim, Yonggang Chosun University Department of Computer Engineering Korea Republic of Dongseo University Department of Software Korea Republic of Kongju National University Division of Computer Science and Engineering Korea Republic of

ISBN: (纸本)9798350335385

Reconfigurable intelligent surface (RIS) is one of the promising technology for the next-generation wireless networks. The RIS reflects the received signal with phase shift introduced by reflecting elements without analog to digital conversion. In relay transmission scenario, RIS could be exploited to enhance the network coverage and improve transmission performance. In this paper, we consider RIS-assisted full-duplex (FD) relay transmission scenario. In the considered scenario, RIS and FD relay node performs relay transmission. Although the beamformed signal could be generated by phase shift of RIS, the interference from RIS to FD relay node may degrade the throughput performance. The proposed method cancels both of interference from RIS and self-interference at the FD relay node by estimating interference channels in the preparation phase before data transmission. © 2023 IEEE.

关键词： Analog to digital conversion

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OUT OF THE LAB AND INTO THE FIELD - SYSTEM-DESIGN OF LARGE EXPERT SYSTEMS

OUT OF THE LAB AND INTO THE FIELD - SYSTEM-DESIGN OF LARGE E...

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INTERNATIONAL CONF ON DEVELOPING AND MANAGING EXPERT SYSTEM PROGRAMS

作者： GARRETT, R Computer and Software Engineering Division Institute for Defense Analyses 1801 N.Beauregard St. Alexandria 22311 VA United States

ISBN: (纸本)0818622504

Traditional software engineering is crucial to the successful development and deployment of a large expert system. In this respect, large expert systems are shown to have many similarities with other large software systems. The advanced computing concepts, rapid prototyping approach, and general research and development aspects of expert systems have sometimes led to the neglect of fundamental principles of software engineering. These principles are creating and maintaining interfaces between program modules, the use of specification languages, automatic code generation, long-term maintenance, and the use of commercial products. A large-scale expert system currently in advanced development is used as an example. © 1991 IEEE.

关键词： Expert systems

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Search and Recommendation Systems with Metadata Extensions 26

Search and Recommendation Systems with Metadata Extensions

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26th International Conference on Advanced Communications Technology, ICACT 2024

作者： Kim, Woo-Hyeon Kim, Joo-Chang Kyonggi University Division of Ai Computer Science and Computer Engineering Korea Republic of Contents Convergence Software Research Institute Kyonggi University Korea Republic of

ISBN: (纸本)9791188428120

This paper proposes an AI-based video metadata extension model to overcome the limitations of video search and recommendation systems in the multimedia industry. Current video searches and recommendations utilize pre-added metadata. Metadata includes filenames, keywords, tags, genres, etc. This makes it impossible to make direct predictions about the content of a video without pre-added metadata. These platforms also analyze your previous search history, viewing history, etc. to understand your interests in order to serve you personalized videos. This may not reflect the actual content and may raise privacy concerns. In addition, recommendation systems suffer from a cold start problem, which is the lack of an initial target, as well as a bubble effect. Therefore, this study proposes a search and recommendation system by expanding metadata in videos using techniques such as shot boundary detection, speech recognition, and text mining. The proposed method selects the main objects required by the recommendation system based on the object frequency and extracts the corresponding objects from the video frame by frame. In addition, we extract the speech from the video separately, convert the speech to text to extract the script and apply text mining techniques to the extracted script to quantify it. Then, we synchronize the object frequency and the transcript to create a single contextual data. After that, we group videos and clips based on the contextual data and index them. Finally, we utilize Shot Boundary Detection to segment videos based on their content. To ensure that the generated contextual data is appropriate for the video, the proposed model compares the extracted script with the video's subtitle data to check and calibrate its accuracy. The model can then be fine-tuned by tuning and cross-validating the hyperparameter to improve its performance. These models can be incorporated into a variety of content discovery and recommendation platforms. By using expanded

关键词： Speech recognition

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A Feature Fusion-Based Approach for Mammographic Mass Classification Using Deep Learning 1

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5th International Conference on Innovative Computing, IC 2022

作者： ur Rehman, Khalil Li, Jianqiang Pei, Yan Yasin, Anaa Ali, Saqib Saeed, Yousaf School of Software Engineering Beijing University of Technology Beijing China Beijing Engineering Research Center for IoT Software and Systems Beijing China Computer Science Division University of Aizu Aizuwakamatsu Japan

ISBN: (数字)9789811941320

ISBN: (纸本)9789811941313

Breast cancer seems to be the most deadly cancer for females globally. Mammographic masse detection is essential for the early diagnosis of breast cancer. The manual detection of breast masses using texture analysis from digital mammograms is hard because of its diverse patterns. Automatic detection of breast masses from mammograms with computer algorithms at early phases could help physicians to avoid unnecessary biopsies. In the current study, we investigated the limitations of texture analysis for mass detection by creating an MR taxon filter bank using Laplacian of Gaussian. We created a deep taxon feature fusion bank for the EfficinetNet DCNN to classify benign and malignant masses. The experimental results were examined on the public CBIS-DDSM and the local PINUM dataset. Our method yielded 0.96 and 0.98 accuracies, respectively. The results findings illustrated that our method significantly outperformed than the MobileNet, AlexNet, DenseNet, and previous studies. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mammography

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