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Numerical Analysis and Scientific Computing Commons™

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2023

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Articles 31 - 60 of 341

Full-Text Articles in Numerical Analysis and Scientific Computing

Designing An Overseas Experiential Course In Data Science, Hua Leong Fwa, Graham Ng Dec 2023

Designing An Overseas Experiential Course In Data Science, Hua Leong Fwa, Graham Ng

Research Collection School Of Computing and Information Systems

Unprecedented demand for data science professionals in the industry has led to many educational institutions launching new data science courses. It is however imperative that students of data science programmes learn through execution of real-world, authentic projects on top of acquiring foundational knowledge on the basics of data science. In the process of working on authentic, real-world projects, students not only create new knowledge but also learn to solve open, sophisticated, and ill-structured problems in an inter-disciplinary fashion. In this paper, we detailed our approach to design a data science curriculum premised on learners solving authentic data science problems sourced …

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Offline Rl With Discrete Proxy Representations For Generalizability In Pomdps, Pengjie Gu, Xinyu Cai, Dong Xing, Xinrun Wang, Mengchen Zhao, Bo An Dec 2023

Offline Rl With Discrete Proxy Representations For Generalizability In Pomdps, Pengjie Gu, Xinyu Cai, Dong Xing, Xinrun Wang, Mengchen Zhao, Bo An

Research Collection School Of Computing and Information Systems

Offline Reinforcement Learning (RL) has demonstrated promising results in various applications by learning policies from previously collected datasets, reducing the need for online exploration and interactions. However, real-world scenarios usually involve partial observability, which brings crucial challenges of the deployment of offline RL methods: i) the policy trained on data with full observability is not robust against the masked observations during execution, and ii) the information of which parts of observations are masked is usually unknown during training. In order to address these challenges, we present Offline RL with DiscrEte pRoxy representations (ORDER), a probabilistic framework which leverages novel state …

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Peer Learning In An Undergraduate Linear Algebra Course - A Social Network Analysis, Manoj Thulasidas, Kyong Jin Shim, Jonathan Teo Dec 2023

Peer Learning In An Undergraduate Linear Algebra Course - A Social Network Analysis, Manoj Thulasidas, Kyong Jin Shim, Jonathan Teo

Research Collection School Of Computing and Information Systems

This study employs Social Network Analysis (SNA) to explore peer learning behaviors among undergraduate Linear Algebra students. By examining the relational dynamics within the classroom, SNA unveils patterns of interaction, information flow, and collaboration among students. Our analysis identifies the prevalence and evolution of peer learning, and how it influences the students' academic performance. It also unveils the attributes of the students who engage in peer helping and the formation of small communities through such interactions. The findings of the study can provide valuable insights for educators aiming to enhance peer learning and improve educational practices in Linear Algebra and …

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Knowledge Graph Enhanced Aspect-Based Sentiment Analysis Incorporating External Knowledge, Autumn Teo, Zhaoxia Wang, Haibo Pen, Budhitama Subagdja, Seng-Beng Ho, Boon Kiat Quek Dec 2023

Knowledge Graph Enhanced Aspect-Based Sentiment Analysis Incorporating External Knowledge, Autumn Teo, Zhaoxia Wang, Haibo Pen, Budhitama Subagdja, Seng-Beng Ho, Boon Kiat Quek

Research Collection School Of Computing and Information Systems

Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentiment analysis. To better comprehend long complicated sentences and obtain accurate aspect-specific information, linguistic and commonsense knowledge are generally required in this task. However, most current methods employ complicated and inefficient approaches to incorporate external knowledge, e.g., directly searching the graph nodes. Additionally, the complementarity between external knowledge and linguistic information has not been thoroughly studied. To this end, we propose a knowledge graph augmented network (KGAN), which aims to effectively incorporate external knowledge with explicitly syntactic and contextual information. In particular, KGAN captures the sentiment feature representations from multiple different …

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Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu Nov 2023

Application Of Virtual-Real Simulation In Military Field, Ziquan Mao, Jialong Gao, Jianxing Gong, Quan Liu

Journal of System Simulation

Abstract: The definition and content of the virtual-real simulation are presented. According to different technical ideas, the development status and existing problems of virtual-real simulation are summarized from three aspects of digital twin, live-virtual-constructive (LVC) simulation, and parallel system. The similarities and differences, as well as the advantages and disadvantages of the three methods are analyzed and compared, and their main application fields are discussed. In order to deal with difficulties encountered in military training, operational tests, equipment development, and equipment maintenance, a solution based on virtual-real simulation is proposed by means of theoretical guidance, case comparison, and transfer and …

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Research On Multi-Process Product Quality Prediction Based On Improved Bilstm, Tianrui Zhang, Yuting Liu, Yike Wang Nov 2023

Research On Multi-Process Product Quality Prediction Based On Improved Bilstm, Tianrui Zhang, Yuting Liu, Yike Wang

Journal of System Simulation

Abstract: In response to the complex manufacturing process of multi-process products, a multi-process product quality prediction model based on the kernel principal component analysis (KPCA) - and improved sparrow search algorithm (ISSA) optimized bi-directional long short term memory (BiLSTM) was proposed to address the uncertain factors that affect product quality, while improving the capacity for each process and ensuring the stability, in multi-process production. Firstly, KPCA was used for data preprocessing, and a kernel function was established on the basis of principal component analysis together with kernel methods. As redundant features were removed through dimension reduction, an improved Gaussian mutation …

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The Propagation And Execution Of Malware In Images, Piper Hall Nov 2023

The Propagation And Execution Of Malware In Images, Piper Hall

Cybersecurity Undergraduate Research Showcase

Malware has become increasingly prolific and severe in its consequences as information systems mature and users become more reliant on computing in their daily lives. As cybercrime becomes more complex in its strategies, an often-overlooked manner of propagation is through images. In recent years, several high-profile vulnerabilities in image libraries have opened the door for threat actors to steal money and information from unsuspecting users. This paper will explore the mechanisms by which these exploits function and how they can be avoided.

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Adaptive Robust Trajectory Tracking Control For Nsv With Multiple Stochastic Disturbances, Xiaohu Yan, Yuwu Yao, Yuhua Wu, Jiangxin Xu Nov 2023

Adaptive Robust Trajectory Tracking Control For Nsv With Multiple Stochastic Disturbances, Xiaohu Yan, Yuwu Yao, Yuhua Wu, Jiangxin Xu

Journal of System Simulation

Abstract: A stochastic control scheme of adaptive robust trajectory tracking is proposed for near space vehicle (NSV) with stochastic noise input disturbances, Poisson random fluctuation disturbances, and control input saturation. The effective tracking of the height and speed reference signals is realized. For the outer loop trajectory control, the robust stochastic controller is designed for the height subsystem and the speed subsystem respectively. Additionally, the required attitude angle reference signals for the inner loop attitude control are obtained by converting the equivalent control input via numerical calculation. For the inner loop attitude control problems, an adaptive robust stochastic control scheme …

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Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang Nov 2023

Image Semantic Segmentation Algorithm Based On Improved Deeplabv3+, Weiping Zhao, Yu Chen, Song Xiang, Yuanqiang Liu, Chaoyue Wang

Journal of System Simulation

Abstract: Mainstream image semantic segmentation networks currently face problems such as incorrec segmentation, discontinuous segmentation, and high model complexity, which cannot be flexibly and efficiently deployed in practical scenarios. To this end, an image semantic segmentation network that optimizes the DeepLabv3+ model is designed by comprehensively considering the network parameters, prediction time, and accuracy. The lightweight EfficientNetv2 is adopted to extract backbone network features and improve parameter utilization. In the atrous spatial pyramid pooling module, the mixed strip pooling is utilized to replace the global average pooling, and a depthwise separable dilated convolution is introduced to reduce parameters and improve …

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Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma Nov 2023

Intercell Dynamic Scheduling Method Based On Deep Reinforcement Learning, Jing Ni, Mengke Ma

Journal of System Simulation

Abstract: In order to solve the intercell scheduling problem of dynamic arrival of machining tasks and realize adaptive scheduling in the complex and changeable environment of the intelligent factory, a scheduling method based on a deep Q network is proposed. A complex network with cells as nodes and workpiece intercell machining path as directed edges is constructed, and the degree value is introduced to define the state space with intercell scheduling characteristics. A compound scheduling rule composed of a workpiece layer, unit layer, and machine layer is designed, and hierarchical optimization makes the scheduling scheme more global. Since double deep …

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Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao Nov 2023

Analysis Of Autonomous Aerial Refueling Capability Requirements And Key Evaluation Indicators, Quan Zou, Yixin Hua, Zhu Shao, Wenbi Zhao

Journal of System Simulation

Abstract: From the perspective of flight tests, how to evaluate the autonomous aerial refueling (AAR) capability and select key indicators for evaluation is a key problem to be solved for AAR trials. The standards requirements of aerial refueling and manned aircraft aerial refueling experience in China and abroad are analyzed. The total capability of AAR is studied, and key evaluation indicators in the AAR whole process including rendezvous, formation, docking, refueling, and disengagement are proposed. The evaluation method is demonstrated in both numerical simulation and hardware-in-loop test environments. Finally, the key indicators affecting the docking success of AAR are analyzed, …

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Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao Nov 2023

Imitative Generation Of Optimal Guidance Law Based On Reinforcement Learning, Zhengxuan Jia, Tingyu Lin, Yingying Xiao, Guoqiang Shi, Hao Wang, Bi Zeng, Yiming Ou, Pengpeng Zhao

Journal of System Simulation

Abstract: Under the background of high-speed maneuvering target interception, an optimal guidance law generation method for head-on interception independent of target acceleration estimation is proposed based on deep reinforcement learning. In addition, its effectiveness is verified through simulation experiments. As the simulation results suggest, the proposed method successfully achieves head-on interception of high-speed maneuvering targets in 3D space and largely reduces the requirement for target estimation with strong uncertainty, and it is more applicable than the optimal control method.

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A Cellular Automata Model For Simulating Ships Passing Through Waterways With Alternating Wide And Narrow Sections, Yulong Sun, Jianfeng Zheng, Jiaxuan Han, Chao Li Nov 2023

A Cellular Automata Model For Simulating Ships Passing Through Waterways With Alternating Wide And Narrow Sections, Yulong Sun, Jianfeng Zheng, Jiaxuan Han, Chao Li

Journal of System Simulation

Abstract: For improving the traffic efficiency of wide and narrow alternating waterways, considering Kiel Canal as an example, according to the structural characteristics of Kiel Canal with alternating width and narrow sections, a two-way ship traffic flow cellular automata model is established, and the simulation of ships passing through Kiel Canal is studied. Cellular space is set up according to the actual structure of Kiel Canal, and the evolution rules are set up based on the fixed block theory and moving block theory. In particular, due to the structure of Kiel Canal, large ships cannot pass simultaneously in the narrow …

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Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive Convolutional Neural Network, Wenfeng Zhang, Zhichao Zhu, Dinghui Wu Nov 2023

Rolling Bearing Fault Diagnosis Based On Weighted Domain Adaptive Convolutional Neural Network, Wenfeng Zhang, Zhichao Zhu, Dinghui Wu

Journal of System Simulation

Abstract: A rolling bearing fault diagnosis method based on a weighted domain adaptive convolutional neural network (WDACNN) is proposed to solve the problem that the data distribution of vibration signals of rolling bearings changes due to workload changes, which leads to poor generalization of fault diagnosis algorithm. In this method, the domain adaptation algorithm is embedded in the convolutional neural network to make the classifier based on the source domain achieve excellent generalization in the target domain, and the weight coefficient is introduced to weight the samples in the source domain to reduce the influence of the class weight deviation. …

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Multi-Depot Half-Open Vehicle Routing Problem With Simultaneous Delivery-Pickup And Time Windows, Yingyu Zhang, Liyun Wu, Shengtai Jia Nov 2023

Multi-Depot Half-Open Vehicle Routing Problem With Simultaneous Delivery-Pickup And Time Windows, Yingyu Zhang, Liyun Wu, Shengtai Jia

Journal of System Simulation

Abstract: To solve the multi-depot half-open vehicle routing problem with simultaneous delivery-pickup and time windows, this paper builds a mathematical model of a multi-depot half-open vehicle routing problem with simultaneous delivery-pickup and time windows by balancing the vehicle in and out of the distribution center and minimizing vehicle delivery distance as the goal. According to the characteristics of the problem, a brain storm algorithm based on chaotic mutation is designed to solve this problem,and the sequential crossover strategy is adopted to increase the population diversity. Meanwhile, the algorithm selects two chaotic maps for chaotic mutation operation, which employs the diversity, …

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Charging Facility Layouts Based On Charging Selection Behavior, Lixiao Wang, Zhonghui Wang Nov 2023

Charging Facility Layouts Based On Charging Selection Behavior, Lixiao Wang, Zhonghui Wang

Journal of System Simulation

Abstract: A charging facility layout method based on charging selection behavior is proposed for the current uncoordinated development of electric vehicles and charging infrastructure and the low utilization of public charging facilities. The influence of the charging selection behavior of electric vehicle users' trips on the charging facility layout is considered, and a charging selection behavior model is built and applied to the charging demand prediction. Based on the study of charging selection behavior and charging demands, a charging facility layout model with the minimization of total travel time as the objective function is built, and the reciprocal feedback between …

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Uav-Enabled Task Offloading Strategy For Vehicular Edge Computing Networks, Feng Hu, Haiyang Gu, Jun Lin Nov 2023

Uav-Enabled Task Offloading Strategy For Vehicular Edge Computing Networks, Feng Hu, Haiyang Gu, Jun Lin

Journal of System Simulation

Abstract: As intelligent vehicles are equipped with more and more sensors, the explosive growth of sensor data is generated, which brings severe challenges to vehicular communication and computing. In addition, the modern road presents a three-dimensional structure, and the system architecture of traditional vehicular networks cannot guarantee full coverage and seamless computing. A task offloading strategy for UAV-assisted and 6G-enabled (Sixth Generation) vehicular edge computing networks is proposed. Furthermore, a flexible and intelligent vehicular edge computing mode is composed by vehicles and UAVs, which provide three-dimensional edge computing services for delay-sensitive and computation-intensive vehicular tasks, and ensure timely processing and …

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Development Of Combat Concept Of Intelligent Land Assault System Based On Dodaf, Can Wang, Haoran Ji, Qisheng Guo, Zhiming Dong, Yaxin Tan, Ge Mu Nov 2023

Development Of Combat Concept Of Intelligent Land Assault System Based On Dodaf, Can Wang, Haoran Ji, Qisheng Guo, Zhiming Dong, Yaxin Tan, Ge Mu

Journal of System Simulation

Abstract: In view of military demand traction in the development of land assault equipment, a combat concept of land assault systems for future intelligent combat is developed. Basedon the definition of relevant concepts and research boundaries, the combat concept model framework and modeling steps are proposed based on DoDAF, and the combat effect, combat process, combat nodes, resource interaction, system composition, and capability characteristics are analyzed in combination with the model description. The combat concept verification is carried out from the aspects of system combat efficiency and communication load by simulation experiments. The results show that the intelligent assault system …

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Research On Operational Effectiveness Evaluation Method Of Space-Based Information Support Equipment System, Xiaolan Yu, Wei Xiong, Chi Han, Zhenwei Wu Nov 2023

Research On Operational Effectiveness Evaluation Method Of Space-Based Information Support Equipment System, Xiaolan Yu, Wei Xiong, Chi Han, Zhenwei Wu

Journal of System Simulation

Abstract: The operational effectiveness evaluation of space-based information support equipment systems has become a research hotspot in the military field. How to effectively deal with the nonlinear and confrontational problems of the operational effectiveness of the space-based information support equipment system has become a crucial issue in the development of the space-based information support equipment system. In this paper, a method for evaluating the operational effectiveness of the space-based information support equipment system based on the system dynamics (SD) model is presented. The SD flow rate basic tree entry modeling method is used to establish the basic tree entry model …

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Requirements Of Parallel Combat System Based On Gqfd-Coupling Coordination Degree, Zhiming Dong, Bingshan Si, Liang Li Nov 2023

Requirements Of Parallel Combat System Based On Gqfd-Coupling Coordination Degree, Zhiming Dong, Bingshan Si, Liang Li

Journal of System Simulation

Abstract: In view of future intelligent unmanned combat characteristics, the concept of parallel combat is proposed and the model of parallel combat system is built based on OODA ring theory. Meanwhile, this paper builds a demand analysis model based on GQFD-coupling coordination degree to solve the low reliability, lack of objectivity, and single description perspective of the traditional quality function deployment (QFD) method and coupling coordination degree analysis during demand analysis. Additionally, the importance ranking of ability requirements in the parallel combat system is obtained by the house of quality of ability requirement analysis in the combat system based on …

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Learning-Based Ant Colony Optimization Algorithm For Solving A Kind Of Complex 2-Echelon Vehicle Routing Problem, Xue Chen, Rong Hu, Hui Wang, Zuocheng Li, Bin Qian, Yixu Li Nov 2023

Learning-Based Ant Colony Optimization Algorithm For Solving A Kind Of Complex 2-Echelon Vehicle Routing Problem, Xue Chen, Rong Hu, Hui Wang, Zuocheng Li, Bin Qian, Yixu Li

Journal of System Simulation

Abstract: Aiming at green 2-echelon vehicle routing problem with simultaneous pick-up and delivery, a learning-based ant colony optimization algorithm combined with clustering decomposition is proposed. The objective function to be minimized is total transportation cost wherein carbon emission cost is specially considered. Associated with the mutual coupling features of the 2-echelon vehicle routing problem, we propose a distance-based clustering method to decompose the original problem into a set of sub-problems. Then, a learning-based ant colony optimization algorithm is presented to find the solutions of the sub-problems based on which the solution of the original problem can be obtained. In the …

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Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer Nov 2023

Physics-Informed Neural Networks For Agent-Based Epidemiological Model Calibration, Alvan C. Arulandu, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

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Application Of Physics Informed Neural Networks For Predicting Disease Dynamics, Alonso Gabriel Ogueda, Padmanabhan Seshaiyer Nov 2023

Application Of Physics Informed Neural Networks For Predicting Disease Dynamics, Alonso Gabriel Ogueda, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

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Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja Nov 2023

Optimizing Uncertainty Quantification Of Vision Transformers In Deep Learning On Novel Ai Architectures, Erik Pautsch, John Li, Silvio Rizzi, George K. Thiruvathukal, Maria Pantoja

Computer Science: Faculty Publications and Other Works

Deep Learning (DL) methods have shown substantial efficacy in computer vision (CV) and natural language processing (NLP). Despite their proficiency, the inconsistency in input data distributions can compromise prediction reliability. This study mitigates this issue by introducing uncertainty evaluations in DL models, thereby enhancing dependability through a distribution of predictions. Our focus lies on the Vision Transformer (ViT), a DL model that harmonizes both local and global behavior. We conduct extensive experiments on the ImageNet-1K dataset, a vast resource with over a million images across 1,000 categories. ViTs, while competitive, are vulnerable to adversarial attacks, making uncertainty estimation crucial for …

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Heterogeneous Graph Neural Network With Multi-View Representation Learning, Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu Nov 2023

Heterogeneous Graph Neural Network With Multi-View Representation Learning, Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu

Research Collection School Of Computing and Information Systems

In recent years, graph neural networks (GNNs)-based methods have been widely adopted for heterogeneous graph (HG) embedding, due to their power in effectively encoding rich information from a HG into the low-dimensional node embeddings. However, previous works usually easily fail to fully leverage the inherent heterogeneity and rich semantics contained in the complex local structures of HGs. On the one hand, most of the existing methods either inadequately model the local structure under specific semantics, or neglect the heterogeneity when aggregating information from the local structure. On the other hand, representations from multiple semantics are not comprehensively integrated to obtain …

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Complex Knowledge Base Question Answering: A Survey, Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Zhao Wayne Xin, Ji Rong Wen Nov 2023

Complex Knowledge Base Question Answering: A Survey, Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Zhao Wayne Xin, Ji Rong Wen

Research Collection School Of Computing and Information Systems

Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved great success. However, their performances on complex questions are still far from satisfactory. Therefore, in recent years, researchers propose a large number of novel methods, which looked into the challenges of answering complex questions. In this survey, we review recent advances in KBQA with the focus on solving complex questions, which usually contain multiple subjects, express compound relations, or involve numerical operations. In detail, we begin with introducing the complex KBQA task and …

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Quantumeyes: Towards Better Interpretability Of Quantum Circuits, Shaolun Ruan, Qiang Guan, Paul Griffin, Ying Mao, Yong Wang Nov 2023

Quantumeyes: Towards Better Interpretability Of Quantum Circuits, Shaolun Ruan, Qiang Guan, Paul Griffin, Ying Mao, Yong Wang

Research Collection School Of Computing and Information Systems

Quantum computing offers significant speedup compared to classical computing, which has led to a growing interest among users in learning and applying quantum computing across various applications. However, quantum circuits, which are fundamental for implementing quantum algorithms, can be challenging for users to understand due to their underlying logic, such as the temporal evolution of quantum states and the effect of quantum amplitudes on the probability of basis quantum states. To fill this research gap, we propose QuantumEyes, an interactive visual analytics system to enhance the interpretability of quantum circuits through both global and local levels. For the global-level analysis, …

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Constructing Holistic Spatio-Temporal Scene Graph For Video Semantic Role Labeling, Yu Zhao, Hao Fei, Yixin Cao, Bobo Li, Meishan Zhang, Jianguo Wei, Min Zhang, Tat-Seng Chua Nov 2023

Constructing Holistic Spatio-Temporal Scene Graph For Video Semantic Role Labeling, Yu Zhao, Hao Fei, Yixin Cao, Bobo Li, Meishan Zhang, Jianguo Wei, Min Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

As one of the core video semantic understanding tasks, Video Semantic Role Labeling (VidSRL) aims to detect the salient events from given videos, by recognizing the predict-argument event structures and the interrelationships between events. While recent endeavors have put forth methods for VidSRL, they can be mostly subject to two key drawbacks, including the lack of fine-grained spatial scene perception and the insufficiently modeling of video temporality. Towards this end, this work explores a novel holistic spatio-temporal scene graph (namely HostSG) representation based on the existing dynamic scene graph structures, which well model both the fine-grained spatial semantics and temporal …

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Npf-200: A Multi-Modal Eye Fixation Dataset And Method For Non-Photorealistic Videos, Ziyu Yang, Sucheng Ren, Zongwei Wu, Nanxuan Zhao, Junle Wang, Jing Qin, Shengfeng He Nov 2023

Npf-200: A Multi-Modal Eye Fixation Dataset And Method For Non-Photorealistic Videos, Ziyu Yang, Sucheng Ren, Zongwei Wu, Nanxuan Zhao, Junle Wang, Jing Qin, Shengfeng He

Research Collection School Of Computing and Information Systems

Non-photorealistic videos are in demand with the wave of the metaverse, but lack of sufficient research studies. This work aims to take a step forward to understand how humans perceive nonphotorealistic videos with eye fixation (i.e., saliency detection), which is critical for enhancing media production, artistic design, and game user experience. To fill in the gap of missing a suitable dataset for this research line, we present NPF-200, the first largescale multi-modal dataset of purely non-photorealistic videos with eye fixations. Our dataset has three characteristics: 1) it contains soundtracks that are essential according to vision and psychological studies; 2) it …

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Matk: The Meme Analytical Tool Kit, Ming Shan Hee, Aditi Kumaresan, Nguyen Khoi Hoang, Nirmalendu Prakash, Rui Cao, Roy Ka-Wei Lee Nov 2023

Matk: The Meme Analytical Tool Kit, Ming Shan Hee, Aditi Kumaresan, Nguyen Khoi Hoang, Nirmalendu Prakash, Rui Cao, Roy Ka-Wei Lee

Research Collection School Of Computing and Information Systems

The rise of social media platforms has brought about a new digital culture called memes. Memes, which combine visuals and text, can strongly influence public opinions on social and cultural issues. As a result, people have become interested in categorizing memes, leading to the development of various datasets and multimodal models that show promising results in this field. However, there is currently a lack of a single library that allows for the reproduction, evaluation, and comparison of these models using fair benchmarks and settings. To fill this gap, we introduce the Meme Analytical Tool Kit (MATK), an open-source toolkit specifically …

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