Physical Sciences and Mathematics | Open Access Articles

บทความ: เทคโนโลยีควบคุมมลพิษอากาศที่เกิดจากเตาเผาอิฐมอญเชื้อเพลิงชีวมวลแบบถมทรายหลังเตา, อุกฤต สมัครสมาน, สุกฤษฏิ์พงษ์ ไชยมงคล, คณิต มานะธุระ

Thai Environment

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บทความ: "วอเตอร์ฟุตพริ้นท์ของพื้นที่การบริการลูกค้า"กรณีศึกษาสถานประกอบการธุรกิจโรงแรม จังหวัดภูเก็ต, เดชา สีดูกา

Thai Environment

No abstract provided.

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บทความ: การจัดการและการแปรรูป น้ำมันใช้แล้ว ในภาคครัวเรือน, ปิโยรส ทิพย์มงคล, ณัฐพงศ์ ตันติวิวัฒนพันธ์

Thai Environment

No abstract provided.

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Circulation,Volume 26, No.1, Center For Coastal Physical Oceanography, Old Dominion University, Sönke Dangendorf

CCPO Circulation

Fall 2020 issue of CCPO Circulation featuring the article, "Understanding the Causes and Impact of Sea Level Rise," by Sönke Dangendorf.

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2020 October - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

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Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Fashion trend forecasting is a crucial task for both academia and industry. Although some efforts have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal the real fashion trends. Towards insightful fashion trend forecasting, this work focuses on investigating fine-grained fashion element trends for specific user groups. We first contribute a large-scale fashion trend dataset (FIT) collected from Instagram with extracted time series fashion element records and user information. Furthermore, to effectively model the time series data of fashion elements with rather complex patterns, we propose …

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Activity River: Visualizing Planned And Logged Personal Activities For Reflection, Bon Adriel Aseniero, Charles Perin, Wesley Willett, Anthony Tang, Sheelagh Carpendale

Research Collection School Of Computing and Information Systems

We present Activity River, a personal visualization tool which enables individuals to plan, log, and reflect on their self-defined activities. We are interested in supporting this type of reflective practice as prior work has shown that reflection can help people plan and manage their time effectively. Hence, we designed Activity River based on five design goals (visualize historical and contextual data, facilitate comparison of goals and achievements, engage viewers with delightful visuals, support authorship, and enable flexible planning and logging) which we distilled from the Information Visualization and Human-Computer Interaction literature. To explore our approach's strengths and limitations, we conducted …

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The Virtual Reality Questionnaire Toolkit, Martin Feick, Niko Kleer, Anthony Tang, Anthony Tang

Research Collection School Of Computing and Information Systems

In this work, we present the VRQuestionnaireToolkit, which enables the research community to easily collect subjective measures within virtual reality (VR). We contribute a highly customizable and reusable open-source toolkit which can be integrated in existing VR projects rapidly. The toolkit comes with a pre-installed set of standard questionnaires such as NASA TLX, SSQ and SUS Presence questionnaire. Our system aims to lower the entry barrier to use questionnaires in VR and to significantly reduce development time and cost needed to run pre-, in between- and post-study questionnaires.

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Co-Design And Evaluation Of An Intelligent Decision Support System For Stroke Rehabilitation Assessment, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Badia

Research Collection School Of Computing and Information Systems

Clinical decision support systems have the potential to improve work flows of experts in practice (e.g. therapist's evidence-based rehabilitation assessment). However, the adoption of these systems is challenging, and the gains of these systems have not fully demonstrated yet. In this paper, we identified the needs of therapists to assess patient's functional abilities (e.g. alternative perspectives with quantitative information on patient's exercise motions). As a result, we co-designed and developed an intelligent decision support system that automatically identifies salient features of assessment using reinforcement learning to assess the quality of motion and generate patient-specific analysis. We evaluated this system with …

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Fakepolisher: Making Deepfakes More Detection-Evasive By Shallow Reconstruction, Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Lei Ma, Xiaofei Xie, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu

Research Collection School Of Computing and Information Systems

At this moment, GAN-based image generation methods are still imperfect, whose upsampling design has limitations in leaving some certain artifact patterns in the synthesized image. Such artifact patterns can be easily exploited (by recent methods) for difference detection of real and GAN-synthesized images. However, the existing detection methods put much emphasis on the artifact patterns, which can become futile if such artifact patterns were reduced.Towards reducing the artifacts in the synthesized images, in this paper, we devise a simple yet powerful approach termed FakePolisher that performs shallow reconstruction of fake images through a learned linear dictionary, intending to effectively and …

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Deeprhythm: Exposing Deepfakes With Attentional Visual Heartbeat Rhythms, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

As the GAN-based face image and video generation techniques, widely known as DeepFakes, have become more and more matured and realistic, there comes a pressing and urgent demand for effective DeepFakes detectors. Motivated by the fact that remote visual photoplethysmography (PPG) is made possible by monitoring the minuscule periodic changes of skin color due to blood pumping through the face, we conjecture that normal heartbeat rhythms found in the real face videos will be disrupted or even entirely broken in a DeepFake video, making it a potentially powerful indicator for DeepFake detection. In this work, we propose DeepRhythm, a DeepFake …

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Amora: Black-Box Adversarial Morphing Attack, Run Wang, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

Nowadays, digital facial content manipulation has become ubiquitous and realistic with the success of generative adversarial networks (GANs), making face recognition (FR) systems suffer from unprecedented security concerns. In this paper, we investigate and introduce a new type of adversarial attack to evade FR systems by manipulating facial content, called adversarial morphing attack (a.k.a. Amora). In contrast to adversarial noise attack that perturbs pixel intensity values by adding human-imperceptible noise, our proposed adversarial morphing attack works at the semantic level that perturbs pixels spatially in a coherent manner. To tackle the black-box attack problem, we devise a simple yet effective …

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Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

With the recent advances in voice synthesis, AI-synthesized fake voices are indistinguishable to human ears and widely are applied to produce realistic and natural DeepFakes, exhibiting real threats to our society. However, effective and robust detectors for synthesized fake voices are still in their infancy and are not ready to fully tackle this emerging threat. In this paper, we devise a novel approach, named DeepSonar, based on monitoring neuron behaviors of speaker recognition (SR) system, i.e., a deep neural network (DNN), to discern AI-synthesized fake voices. Layer-wise neuron behaviors provide an important insight to meticulously catch the differences among inputs, …

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Annapurna: An Automated Smartwatch-Based Eating Detection And Food Journaling System, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Maintaining a food journal can allow an individual to monitor eating habits, including unhealthy eating sessions, food items causing severe reactions, or portion size related information. However, manually maintaining a food journal can be burdensome. In this paper, we explore the vision of a pervasive, automated, completely unobtrusive, food journaling system using a commodity smartwatch. We present a prototype system — Annapurna— which is composed of three key components: (a) a smartwatch-based gesture recognizer that can robustly identify eating-specific gestures occurring anywhere, (b) a smartwatch-based image captor that obtains a small set of relevant images (containing views of the food …

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Central Inspection Teams And The Enforcement Of Environmental Regulations In China, C. Xiang, Terry Van Gevelt

Research Collection College of Integrative Studies

Despite the existence of a comprehensive set of environmental regulations, China’s environmental issues continue largely unabated and are increasingly leading to discontent among its citizens. Mirroring recent governance trends in China, the central government has increasingly taken a more hands-on-role to ensure the enforcement of environmental regulations by local government officials. One manifestation of this effort to re-centralize environmental institutions has been the establishment and deployment of Central Environmental Inspection Teams (CEITs). CEITs report directly to the central government and are dispatched to carry out crackdowns where the central government has reason to believe that environmental regulations are not being …

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Hierarchical Identity-Based Signature In Polynomial Rings, Zhichao Yang, Dung H. Duong, Willy Susilo, Guomin Yang, Chao Li, Rongmao Chen

Research Collection School Of Computing and Information Systems

Hierarchical identity-based signature (HIBS) plays a core role in a large community as it significantly reduces the workload of the root private key generator. To make HIBS still available and secure in post-quantum era, constructing lattice-based schemes is a promising option. In this paper, we present an efficient HIBS scheme in polynomial rings. Although there are many lattice-based signatures proposed in recent years, to the best of our knowledge, our HIBS scheme is the first ring-based construction. In the center of our construction are two new algorithms to extend lattice trapdoors to higher dimensions, which are non-trivial and of independent …

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Catch You If You Deceive Me: Verifiable And Privacy-Aware Truth Discovery In Crowdsensing Systems, Guowen Xu, Hongwei Li, Shengmin Xu, Hao Ren, Yonghui Zhang, Jianfei Sun, Robert H. Deng

Research Collection School Of Computing and Information Systems

Truth Discovery (TD) is to infer truthful information by estimating the reliability of users in crowdsensing systems. To protect data privacy, many Privacy-Preserving Truth Discovery (PPTD) approaches have been proposed. However, all existing PPTD solutions do not consider a fundamental issue of trust. That is, if the data aggregator (e.g., the cloud server) is not trustworthy, how can an entity be convinced that the data aggregator has correctly performed the PPTD? A "lazy"cloud server may partially follow the deployed protocols to save its computing and communication resources, or worse, maliciously forge the results for some shady deals. In this paper, …

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Efficient Sampling Algorithms For Approximate Temporal Motif Counting, Jingjing Wang, Yanhao Wang, Wenjun Jiang, Yuchen Li, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

A great variety of complex systems ranging from user interactions in communication networks to transactions in financial markets can be modeled as temporal graphs, which consist of a set of vertices and a series of timestamped and directed edges. Temporal motifs in temporal graphs are generalized from subgraph patterns in static graphs which take into account edge orderings and durations in addition to structures. Counting the number of occurrences of temporal motifs is a fundamental problem for temporal network analysis. However, existing methods either cannot support temporal motifs or suffer from performance issues. In this paper, we focus on approximate …

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Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara

Research Collection School Of Computing and Information Systems

We transform traditional experience writing into in-situ voice-based multimedia authoring. Documenting experiences digitally in blogs and journals is a common activity that allows people to socially connect with others by sharing their experiences (e.g. travelogue). However, documenting such experiences can be time-consuming and cognitively demanding as it is typically done OUT-OF-CONTEXT (after the actual experience). We propose in-situ voice-based multimedia authoring (IVA), an alternative workflow to allow IN-CONTEXT experience documentation. Unlike the traditional approach, IVA encourages in-context content creations using voice-based multimedia input and stores them in multi-modal "snippets". The snippets can be rearranged to form multimedia articles and can …

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Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn: Reproducibility Companion Paper, Quoc Tuan Truong, Hady W. Lauw, Martin Aumuller, Naoko Nitta

Research Collection School Of Computing and Information Systems

We revisit our contributions on visual sentiment analysis for online review images published at ACM Multimedia 2017, where we develop item-oriented and user-oriented convolutional neural networks that better capture the interaction of image features with specific expressions of users or items. In this work, we outline the experimental claims as well as describe the procedures to reproduce the results therein. In addition, we provide artifacts including data sets and code to replicate the experiments.

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Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar

Research Collection School Of Computing and Information Systems

We address the problem of multiple agents finding their paths from respective sources to destination nodes in a graph (also called MAPF). Most existing approaches assume that all agents move at fixed speed, and that a single node accommodates only a single agent. Motivated by the emerging applications of autonomous vehicles such as drone traffic management, we present zone-based path finding (or ZBPF) where agents move among zones, and agents' movements require uncertain travel time. Furthermore, each zone can accommodate multiple agents (as per its capacity). We also develop a simulator for ZBPF which provides a clean interface from the …

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European Floating Strike Lookback Options: Alpha Prediction And Generation Using Unsupervised Learning, Tristan Lim, Aldy Gunawan, Chin Sin Ong

Research Collection School Of Computing and Information Systems

This research utilized the intrinsic quality of European floating strike lookback call options, alongside selected return and volatility parameters, in a K-means clustering environment, to recommend an alpha generative trading strategy. The result is an elegant easy-to-use alpha strategy based on the option mechanisms which identifies investment assets with high degree of significance. In an upward trending market, the research had identified European floating strike lookback call option as an evaluative criterion and investable asset, which would both allow investors to predict and profit from alpha opportunities. The findings will be useful for (i) buy-side investors seeking alpha generation and/or …

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Dual-Slam: A Framework For Robust Single Camera Navigation, Huajian Huang, Wen-Yan Lin, Siying Liu, Dong Zhang, Sai-Kit Yeung

Research Collection School Of Computing and Information Systems

SLAM (Simultaneous Localization And Mapping) seeks to provide a moving agent with real-time self-localization. To achieve real-time speed, SLAM incrementally propagates position estimates. This makes SLAM fast but also makes it vulnerable to local pose estimation failures. As local pose estimation is ill-conditioned, local pose estimation failures happen regularly, making the overall SLAM system brittle. This paper attempts to correct this problem. We note that while local pose estimation is ill-conditioned, pose estimation over longer sequences is well-conditioned. Thus, local pose estimation errors eventually manifest themselves as mapping inconsistencies. When this occurs, we save the current map and activate two …

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Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Combining video streaming and online retailing (V2R) has been a growing trend recently. In this paper, we provide practitioners and researchers in multimedia with a cloud-based platform named Hysia for easy development and deployment of V2R applications. The system consists of: 1) a back-end infrastructure providing optimized V2R related services including data engine, model repository, model serving and content matching; and 2) an application layer which enables rapid V2R application prototyping. Hysia addresses industry and academic needs in large-scale multimedia by: 1) seamlessly integrating state-of-the-art libraries including NVIDIA video SDK, Facebook faiss, and gRPC; 2) efficiently utilizing GPU computation; and …

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Federated Topic Discovery: A Semantic Consistent Approach, Yexuan Shi, Yongxin Tong, Zhiyang Su, Di Jiang, Zimu Zhou, Wenbin Zhang

Research Collection School Of Computing and Information Systems

General-purpose topic models have widespread industrial applications. Yet high-quality topic modeling is becoming increasingly challenging because accurate models require large amounts of training data typically owned by multiple parties, who are often unwilling to share their sensitive data for collaborative training without guarantees on their data privacy. To enable effective privacy-preserving multiparty topic modeling, we propose a novel federated general-purpose topic model named private and consistent topic discovery (PC-TD). On the one hand, PC-TD seamlessly integrates differential privacy in topic modeling to provide privacy guarantees on sensitive data of different parties. On the other hand, PC-TD exploits multiple sources of …

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Compact Bilinear Augmented Query Structured Attention For Sport Highlights Classification, Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Qing Liu, Xiaojun Hu

Research Collection School Of Computing and Information Systems

Understanding fine-grained activities, such as sport highlights, is a problem being overlooked and receives considerably less research attention. Potential reasons include absences of specific fine-grained action benchmark datasets, research preferences to general supercategorical activities classification, and challenges of large visual similarities between fine-grained actions. To tackle these, we collect and manually annotate two sport highlights datasets, i.e., Basketball8 & Soccer-10, for fine-grained action classification. Sample clips in the datasets are annotated with professional sub-categorical actions like “dunk”, “goalkeeping” and etc. We also propose a Compact Bilinear Augmented Query Structured Attention (CBA-QSA) module and stack it on top of general three-dimensional …

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Cross-Domain Cross-Modal Food Transfer, Bin Zhu, Chong-Wah Ngo, Jingjing Chen

Research Collection School Of Computing and Information Systems

The recent works in cross-modal image-to-recipe retrieval pave a new way to scale up food recognition. By learning the joint space between food images and recipes, food recognition is boiled down as a retrieval problem by evaluating the similarity of embedded features. The major drawback, nevertheless, is the difficulty in applying an already-trained model to recognize different cuisines of dishes unknown to the model. In general, model updating with new training examples, in the form of image-recipe pairs, is required to adapt a model to new cooking styles in a cuisine. Nevertheless, in practice, acquiring sufficient number of image-recipe pairs …

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Person-Level Action Recognition In Complex Events Via Tsd-Tsm Networks, Yanbin Hao, Zi-Niu Liu, Hao Zhang, Bin Zhu, Jingjing Chen, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The task of person-level action recognition in complex events aims to densely detect pedestrians and individually predict their actions from surveillance videos. In this paper, we present a simple yet efficient pipeline for this task, referred to as TSD-TSM networks. Firstly, we adopt the TSD detector for the pedestrian localization on each single keyframe. Secondly, we generate the sequential ROIs for a person proposal by replicating the adjusted bounding box coordinates around the keyframe. Particularly, we propose to conduct straddling expansion and region squaring on the original bounding box of a person proposal to widen the potential space of motion …

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Efficient Ciphertext-Policy Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Jiaming Yuan, Guowen Xu, Yingjiu Li, Ximeng Liu, Yinghui Zhang, Zuobin Yang

Research Collection School Of Computing and Information Systems

Traitor tracing scheme is a paradigm to classify the users who illegal use of their decryption keys in cryptosystems. In the ciphertext-policy attribute-based cryptosystem, the decryption key usually contains the users’ attributes, while the real identities are hidden. The decryption key with hidden identities enables malicious users to intentionally leak decryption keys or embed the decryption keys in the decryption device to gain illegal profits with a little risk of being discovered. To mitigate this problem, the concept of blackbox traceability in the ciphertext-policy attribute-based scheme was proposed to identify the malicious user via observing the I/O streams of the …

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Towards Systematically Deriving Defence Mechanisms From Functional Requirements Of Cyber-Physical Systems, Cheah Huei Yoong, Venkata Reddy Palleti, Arlindo Silva, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems

The threats faced by cyber-physical systems (CPSs) in critical infrastructure have motivated the development of different attack detection mechanisms, such as those that monitor for violations of invariants, i.e. properties that always hold in normal operation. Given the complexity of CPSs, several existing approaches focus on deriving invariants automatically from data logs, but these can miss possible system behaviours if they are not represented in that data. Furthermore, resolving any design flaws identified in this process is costly, as the CPS is already built. In this position paper, we propose a systematic method for deriving invariants before a CPS is …

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Full-Text Articles in Physical Sciences and Mathematics

Thai Environment

Thai Environment

บทความ: การจัดการและการแปรรูป น้ำมันใช้แล้ว ในภาคครัวเรือน, ปิโยรส ทิพย์มงคล, ณัฐพงศ์ ตันติวิวัฒนพันธ์

Thai Environment

Circulation,Volume 26, No.1, Center For Coastal Physical Oceanography, Old Dominion University, Sönke Dangendorf

CCPO Circulation

2020 October - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Activity River: Visualizing Planned And Logged Personal Activities For Reflection, Bon Adriel Aseniero, Charles Perin, Wesley Willett, Anthony Tang, Sheelagh Carpendale

Research Collection School Of Computing and Information Systems

The Virtual Reality Questionnaire Toolkit, Martin Feick, Niko Kleer, Anthony Tang, Anthony Tang

Research Collection School Of Computing and Information Systems

Co-Design And Evaluation Of An Intelligent Decision Support System For Stroke Rehabilitation Assessment, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Badia

Research Collection School Of Computing and Information Systems

Fakepolisher: Making Deepfakes More Detection-Evasive By Shallow Reconstruction, Yihao Huang, Felix Juefei-Xu, Run Wang, Qing Guo, Lei Ma, Xiaofei Xie, Jianwen Li, Weikai Miao, Yang Liu, Geguang Pu

Research Collection School Of Computing and Information Systems

Deeprhythm: Exposing Deepfakes With Attentional Visual Heartbeat Rhythms, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Wei Feng, Yang Liu, Jianjun Zhao

Research Collection School Of Computing and Information Systems

Amora: Black-Box Adversarial Morphing Attack, Run Wang, Felix Juefei-Xu, Qing Guo, Yihao Huang, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

Deepsonar: Towards Effective And Robust Detection Of Ai-Synthesized Fake Voices, Run Wang, Felix Juefei-Xu, Yihao Huang, Qing Guo, Xiaofei Xie, Lei Ma, Yang Liu

Research Collection School Of Computing and Information Systems

Annapurna: An Automated Smartwatch-Based Eating Detection And Food Journaling System, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Central Inspection Teams And The Enforcement Of Environmental Regulations In China, C. Xiang, Terry Van Gevelt

Research Collection College of Integrative Studies

Hierarchical Identity-Based Signature In Polynomial Rings, Zhichao Yang, Dung H. Duong, Willy Susilo, Guomin Yang, Chao Li, Rongmao Chen

Research Collection School Of Computing and Information Systems

Catch You If You Deceive Me: Verifiable And Privacy-Aware Truth Discovery In Crowdsensing Systems, Guowen Xu, Hongwei Li, Shengmin Xu, Hao Ren, Yonghui Zhang, Jianfei Sun, Robert H. Deng

Research Collection School Of Computing and Information Systems

Efficient Sampling Algorithms For Approximate Temporal Motif Counting, Jingjing Wang, Yanhao Wang, Wenjun Jiang, Yuchen Li, Kian-Lee Tan

Research Collection School Of Computing and Information Systems

Livesnippets: Voice-Based Live Authoring Of Multimedia Articles About Experiences, Hyeongcheol Kim, Shengdong Zhao, Can Liu, Kotaro Hara

Research Collection School Of Computing and Information Systems

Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn: Reproducibility Companion Paper, Quoc Tuan Truong, Hady W. Lauw, Martin Aumuller, Naoko Nitta

Research Collection School Of Computing and Information Systems

Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar

Research Collection School Of Computing and Information Systems

European Floating Strike Lookback Options: Alpha Prediction And Generation Using Unsupervised Learning, Tristan Lim, Aldy Gunawan, Chin Sin Ong

Research Collection School Of Computing and Information Systems

Dual-Slam: A Framework For Robust Single Camera Navigation, Huajian Huang, Wen-Yan Lin, Siying Liu, Dong Zhang, Sai-Kit Yeung

Research Collection School Of Computing and Information Systems

Hysia: Serving Dnn-Based Video-To-Retail Applications In Cloud, Huaizheng Zhang, Yuanming Li, Qiming Ai, Yong Luo, Yonggang Wen, Yichao Jin, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Federated Topic Discovery: A Semantic Consistent Approach, Yexuan Shi, Yongxin Tong, Zhiyang Su, Di Jiang, Zimu Zhou, Wenbin Zhang

Research Collection School Of Computing and Information Systems

Compact Bilinear Augmented Query Structured Attention For Sport Highlights Classification, Yanbin Hao, Hao Zhang, Chong-Wah Ngo, Qing Liu, Xiaojun Hu

Research Collection School Of Computing and Information Systems

Cross-Domain Cross-Modal Food Transfer, Bin Zhu, Chong-Wah Ngo, Jingjing Chen

Research Collection School Of Computing and Information Systems

Person-Level Action Recognition In Complex Events Via Tsd-Tsm Networks, Yanbin Hao, Zi-Niu Liu, Hao Zhang, Bin Zhu, Jingjing Chen, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Efficient Ciphertext-Policy Attribute-Based Encryption With Blackbox Traceability, Shengmin Xu, Jiaming Yuan, Guowen Xu, Yingjiu Li, Ximeng Liu, Yinghui Zhang, Zuobin Yang

Research Collection School Of Computing and Information Systems

Towards Systematically Deriving Defence Mechanisms From Functional Requirements Of Cyber-Physical Systems, Cheah Huei Yoong, Venkata Reddy Palleti, Arlindo Silva, Christopher M. Poskitt

Research Collection School Of Computing and Information Systems