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Deep Semantic and Attentive Network for Unsupervised Video Summarization

ACM Transactions on Multimedia Computing, Communications and Applications 2022年第2期18卷 1-21页

作者： Zhong, Sheng-Hua Lin, Jingxu Lu, Jianglin Fares, Ahmed Ren, Tongwei College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical Engineering Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Cairo Egypt State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

With the rapid growth of video data, video summarization is a promising approach to shorten a lengthy video into a compact version. Although supervised summarization approaches have achieved state-of-the-art performance, they require frame-level annotated labels. Such an annotation process is time-consuming and tedious. In this article, we propose a novel deep summarization framework named Deep Semantic and Attentive Network for Video Summarization (DSAVS) that can select the most semantically representative summary by minimizing the distance between video representation and text representation without any frame-level labels. Another challenge associated with video summarization tasks mainly originates from the difficulty of considering temporal information over a long time. Long Short-Term Memory (LSTM) performs well for temporal dependencies modeling but does not work well with long video clips. Therefore, we introduce a self-attention mechanism into our summarization framework to capture the long-range temporal dependencies among the frames. Extensive experiments on two popular benchmark datasets, i.e., SumMe and TVSum, show that our proposed framework outperforms other state-of-the-art unsupervised approaches and even most supervised methods. © 2022 Association for Computing Machinery.

关键词： Semantics

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Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization 1

Enhancing generality of meta-heuristic algorithms through ad...

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1st International Conference on Information and Communications Technology, ICOIACT 2018

作者： Zamli, Kamal Z. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan Pahang Malaysia

ISBN: (纸本)9781538609545

Solving complex optimization problems can be painstakingly difficult endeavor considering multiple and conflicting design goals. A growing trend in utilizing meta-heuristic algorithms to solve these problems has been observed as they have shown considerable success in dealing with tradeoffs between conflicting design goals. Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). Much of these algorithms have adopted elegant metaphors (e.g. heating and cooling of metals in the case of SA and swarming of flocking birds in the case of PSO) from nature in order to derive the mathematical models for generating the solution as well as provides control over their exploration (i.e. sufficient roaming of the search space) and exploitation (i.e. using known knowledge of the surroundings). In line with the no free lunch theorem (), this paper argues that rather than focusing on designing new algorithm, new research should focus on adaptive hybridization of meta-heuristics algorithms in order to compensate the limitation of one with the strengths of another. In this paper, we review the meta-heuristic and hyper-heuristic algorithms in order to highlight the current-state-of-the-arts and suggest areas for future research. © 2018 IEEE.

关键词： Simulated annealing

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Implementation evaluation of Cuckoo search for the benchmark Rosenbrock test function 8th

Implementation evaluation of Cuckoo search for the benchmark...

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8th International Conference on Information Technology, ICIT 2017

作者： Beneoluchi Odili, Julius Romli, Awanis Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan26300 Malaysia

ISBN: (纸本)9781509063321

This paper presents the implementation evaluation of the benchmark Rosenbrock test function with particular emphasis on the effect of the search population and iterations count in the Cuckoo Search algorithm's quest for good solutions. After a number of experimental procedures, this study reveals that deploying a population of 10 nests is sufficient to obtain good solutions to the Rosenbrock test function (or any similar problem to this test landscape). In fact, increasing the search population to 50 nests was a demerit to the Cuckoo Search as it resulted in longer processing time and worse outcomes. In terms of the iteration count, it was discovered that the Cuckoo Search can obtain good results in as little as 100 to 10,000 iterations. The outcome of this study is beneficial to the research community as it will help in facilitating the choice of parameters whenever one is confronted with a similar problem. © 2017 IEEE.

关键词： Iterative methods

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SOLAS: Superpositioning an Optical Lens in Automotive Simulation

arXiv

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arXiv 2025年

作者： Jakab, Daniel Barthel, Julian Braun, Alexander Mohandas, Reenu Deegan, Brian Michael Kumbham, Mahendar Molloy, Dara Collins, Fiachra Scanlan, Anthony Eising, Ciarán Dept. of Electronic and Computer Engineering University of Limerick Castletroy Co. Limerick V94 T9PX Ireland Faculty of Electrical Engineering & Information Technology University of Applied Sciences Düsseldorf40476 Germany Dept. of Electrical and Electronic Engineering University of Galway GalwayH91 TK33 Ireland Valeo Vision Systems Tuam GalwayDY1 22DJ Ireland Lero the Science Foundation Ireland Research Centre for Software University of Limerick LimerickV94 T9PX Ireland

Automotive Simulation is a potentially cost-effective strategy to identify and test corner case scenarios in automotive perception. Recent work has shown a significant shift in creating realistic synthetic data for road traffic scenarios using a video graphics engine. However, a gap exists in modeling realistic optical aberrations associated with cameras in automotive simulation. This paper builds on the concept from existing literature to model optical degradations in simulated environments using the Python-based ray-tracing library KrakenOS. As a novel pipeline, we degrade automotive fisheye simulation using an optical doublet with +/-2◦ Field of View(FOV), introducing realistic optical artifacts into two simulation images from SynWoodscape and Parallel Domain Woodscape. We evaluate KrakenOS by calculating the Root Mean Square Error (RMSE), which averaged around 0.023 across the RGB light spectrum compared to Ansys Zemax OpticStudio, an industrial benchmark for optical design and simulation. Lastly, we measure the image sharpness of the degraded simulation using the ISO12233:2023 Slanted Edge Method and show how both qualitative and measured results indicate the extent of the spatial variation in image sharpness from the periphery to the center of the degradations. © 2025, CC BY.

关键词： Ray tracing

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A Review of Artificial Intelligence in Serious Game for Public Health 3

A Review of Artificial Intelligence in Serious Game for Publ...

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3rd International Conference on Computational Science and Information Management, ICoCSIM 2019

作者： Rafiq, Abdul Asmawaty Abdul Kadir, Tuty Normaziah Ihsan, Siti Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Pahang Kuantan Malaysia

Serious games used in public health for purposes including training, learning, prediction, coaching, diagnostic, rehabilitation and supporting. However, the serious game focuses mainly on user experience and graphical application, but less attention on applying artificial intelligence (AI). By enhancing artificial intelligence, it will have the capability to solve issues, especially in the field of public health. This article discussed a review of the use of artificial intelligence in a serious game for public health. The main idea of this paper is to gather all the related articles and create a trend analysis of the use of Artificial Intelligence (AI) in a serious game for public health. The related articles were applied to Artificial intelligence (AI) in the area of decision-making. The final section discussed the new trend and the future of Artificial intelligence using current AI techniques. © Published under licence by IOP Publishing Ltd.

关键词： Public health

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Russian Language Datasets in the Digital Humanities Domain and Their Evaluation with Word Embeddings 1

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20th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2019

作者： Wohlgenannt, Gerhard Babushkin, Artemii Romashov, Denis Ukrainets, Igor Maskaykin, Anton Shutov, Ilya Faculty of Software Engineering and Computer Systems ITMO University St. Petersburg Russia

ISBN: (数字)9783031243370

ISBN: (纸本)9783031243363

In this paper, we present Russian language datasets in the digital humanities domain for the evaluation of word embedding techniques or similar language modeling and feature learning algorithms. The datasets are split into two task types, word intrusion and word analogy, and contain 31362 task units in total. The characteristics of the tasks and datasets are that they build upon small, domain-specific corpora, and that the datasets contain a high number of named entities. The datasets were created manually for two fantasy novel book series ("A Song of Ice and Fire" and "Harry Potter"). We provide baseline evaluations with popular word embedding models trained on the book corpora for the given tasks, both for the Russian and English language versions of the datasets. Finally, we compare and analyze the results and discuss specifics of Russian language with regards to the problem setting. © 2023, Springer Nature Switzerland AG.

关键词： Embeddings

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Road Enforcement Monitoring System based on Vehicle Type Recognition using Sparse Filtering Convolutional Neural Network with Layer Skipping Strategy (SFCNNLS) 6

Road Enforcement Monitoring System based on Vehicle Type Rec...

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6th IEEE International Conference on Industrial engineering and Applications, ICIEA 2019

作者： Awang, Suryanti Azmi, Nik Mohamad Aizuddin Nik Ghani, Ngahzaifa Ab Faculty of Computer Systems Software Engineering Universiti Malaysia Pahang Kuantan Pahang Malaysia

ISBN: (纸本)9781728108513

Road Enforcement Monitoring System (REMS) is one of the traffic monitoring systems to monitor the enforcement of a specific route for public transportation in cities. The aim of this system is to automatically and efficiently monitor the enforcement to ensure it is adhered by the traffic users. This aim is difficult to be achieved in current practice that relied on human observation by the authorities. Due to that, we proposed to combine REMS with vehicle type recognition (VTR) method known as Sparse-Filtered Convolutional Neural Network with Layer Skipping-strategy (SF-CNNLS). The purpose of using this method is to recognize and classify the vehicles that use the specific route. It is to prevent any vehicle other than public transportations use that route. The output from VTR will be used by REMS to trigger an immediate message to the authorities for further action. The major challenge of our method is to differentiate taxi and bus as public transportations with car and truck. This is because these vehicles have almost similar features. We tested our method with a self-obtained video that captured from a mounted-camera to observe if the challenge is able to be overcome. For the initial stage, the test is deployed on 4 major vehicle classes;car, taxi, truck and bus. The highest accuracy is obtained from car class with 92.5% and an average accuracy is 81.76%. Based on the test, we proved that our method is able to recognize and classify the vehicle classes although the vehicles are sharing almost similar features. © 2019 IEEE.

关键词： Deep learning

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Fabric authenticity method using fast Fourier transformation detection

Fabric authenticity method using fast Fourier transformation...

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1st International Conference on Electrical, Control and computer engineering 2011, InECCE 2011

作者： Ismail, Norislina Syahrir, W.Md. Zain, Jasni M. Tao, Hai Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan 26300 Malaysia

ISBN: (纸本)9781612842288

The authenticity or originality of sport jersey cloth fabric in market nowadays is difficult to distinguish. This is a critical issue that leads to the difficulty for customer to know whether they are purchase the original fabric or the fake one. The purpose of this paper is to develop a prototype for Fabric Authenticity System to judge the originality of jersey cloth fabric based on its pattern structure. Besides this, this study aimed to identify the image processing technique which is Fourier analysis to differentiate the authentic and artificial fabric. As a result, the originality of the fabric can be detected based on the fabric pattern structure itself by looking on its Fourier spectrum. © 2011 IEEE.

关键词： Image processing

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Efficient feature selection analysis for accuracy malware classification 7

Efficient feature selection analysis for accuracy malware cl...

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7th International Conference on Mathematics, Science, and Education 2020, ICMSE 2020

作者： Romli, R.N. Zolkipli, M.F. Osman, M.Z. Faculty of Computer Systems and Software Engineering University Malaysia Pahang Gambang26200 Malaysia

Android is designed for mobile devices and its open-source software. The growth and popularity of android platform are high compared to another platform. Due to its glory, the number of malware has been increasing exponentially. Android system used a permission mechanism to allow users and developers to manage their access to private information, system resources, and data storage required by Android applications (apps). It became an advantage to an attacker to violent the data. This paper proposes a novel framework for Android malware detection. Our framework used three major methods for effective feature representation on malware detection and used this method to classify malware and benign. The result demonstrates that the Random forest is with 23 features is more accurate detection than the other machine learning algorithm. © Published under licence by IOP Publishing Ltd.

关键词： Open source software

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Review on Cost-Value Approach for Requirements Prioritization Techniques 5

Review on Cost-Value Approach for Requirements Prioritizatio...

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5th International Conference on Information Technology, computer and Electrical engineering, ICITACEE 2018

作者： Amelia, Tan Mohamed, Rozlina Binti Faculty of Information System Institut Bisnis Dan Informatika Stikom Surabaya Faculty of Computer Systems and Software Engineering University Malaysia Pahang Surabaya Indonesia Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia

ISBN: (纸本)9781538655276

The use of appropriate requirements prioritization techniques is crucial to the success of a software development project. There are many techniques offered with all the advantages and disadvantages of each. The question that come up frequently when doing requirements prioritization is 'whether the priority list is generated based on customer's required value?' and 'whether the value is generated comparable with the cost incurred for implementation?'. This paper aims to conduct an empirical systematic review to identify and review the requirements prioritization studies based on the cost-value approach. This literature review generates many insights including: reduction of pairwise comparisons, factors and aspects of cost-value, features that support cost value and cost-value constraints. © 2018 IEEE.

关键词： software design

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