Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (972)
- Artificial Intelligence and Robotics (790)
- Computer Engineering (767)
- Numerical Analysis and Scientific Computing (546)
- Databases and Information Systems (436)
-
- Operations Research, Systems Engineering and Industrial Engineering (366)
- Systems Science (317)
- Electrical and Computer Engineering (294)
- Information Security (269)
- Social and Behavioral Sciences (234)
- Software Engineering (228)
- Data Science (166)
- Graphics and Human Computer Interfaces (154)
- Mathematics (149)
- Programming Languages and Compilers (145)
- Theory and Algorithms (144)
- Medicine and Health Sciences (127)
- Other Computer Sciences (125)
- Business (118)
- Education (105)
- Life Sciences (96)
- OS and Networks (93)
- Physics (76)
- Public Affairs, Public Policy and Public Administration (54)
- Arts and Humanities (51)
- Chemistry (46)
- Law (42)
- Systems Architecture (41)
- Institution
-
- Singapore Management University (572)
- China Simulation Federation (315)
- TÜBİTAK (202)
- University of Nebraska - Lincoln (142)
- University of Texas at El Paso (123)
-
- Kennesaw State University (119)
- Old Dominion University (105)
- San Jose State University (85)
- University for Business and Technology in Kosovo (78)
- Technological University Dublin (68)
- Chulalongkorn University (67)
- Zayed University (65)
- Air Force Institute of Technology (54)
- City University of New York (CUNY) (54)
- University of Arkansas, Fayetteville (51)
- Wright State University (46)
- Missouri University of Science and Technology (45)
- Walden University (43)
- University of South Florida (39)
- University of Central Florida (38)
- Boise State University (36)
- MBZUAI (35)
- Portland State University (34)
- Karbala International Journal of Modern Science (33)
- California Polytechnic State University, San Luis Obispo (30)
- Utah State University (30)
- University of Texas at Arlington (28)
- New Jersey Institute of Technology (26)
- University of Kentucky (26)
- Dartmouth College (25)
- Keyword
-
- Deep learning (138)
- Machine learning (130)
- Technical Reports (107)
- UTEP Computer Science Department (107)
- Machine Learning (76)
-
- Deep Learning (61)
- Computer Science (56)
- Artificial intelligence (51)
- COVID-19 (49)
- Cybersecurity (46)
- Blockchain (39)
- Artificial Intelligence (35)
- Computer vision (34)
- Security (31)
- Neural networks (30)
- Optimization (29)
- Reinforcement learning (27)
- Classification (26)
- Simulation (26)
- Privacy (25)
- Department of Computer Science (23)
- Natural language processing (23)
- IoT (22)
- Computer Vision (20)
- Feature extraction (20)
- Transfer learning (20)
- Computer science (19)
- Neural Networks (19)
- Social media (19)
- Visualization (19)
- Publication
-
- Research Collection School Of Computing and Information Systems (545)
- Journal of System Simulation (315)
- Turkish Journal of Electrical Engineering and Computer Sciences (202)
- Theses and Dissertations (147)
- Departmental Technical Reports (CS) (107)
-
- The R Journal (103)
- C-Day Computing Showcase (87)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (67)
- All Works (65)
- Master's Projects (59)
- Computer Science Faculty Publications (46)
- Dissertations (45)
- Walden Dissertations and Doctoral Studies (43)
- USF Tampa Graduate Theses and Dissertations (37)
- Karbala International Journal of Modern Science (33)
- Electronic Theses and Dissertations, 2020-2023 (31)
- Master's Theses (31)
- Articles (30)
- Computer Science Faculty Research & Creative Works (30)
- Browse all Theses and Dissertations (29)
- Computer Science Faculty Publications and Presentations (29)
- Faculty Publications (26)
- Open Educational Resources (25)
- CCAC Theses and Dissertations (24)
- Graduate Theses and Dissertations (24)
- Conference papers (23)
- Electronic Theses and Dissertations (22)
- Computer Vision Faculty Publications (21)
- McKelvey School of Engineering Graduate Student Theses & Dissertations (21)
- Research outputs 2014 to 2021 (21)
- Publication Type
Articles 691 - 720 of 3475
Full-Text Articles in Computer Sciences
(2021 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2021 Revision) Chapter 2: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2021 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2021 Revision) Chapter 1: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2021 Revision) Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2021 Revision) Chapter 3: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
(2021 Revision) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
(2021 Revision) Chapter 5: Essential Aspects Of Physical Design And Implementation Of Relational Databases, Tatiana Malyuta, Ashwin Satyanarayana
Open Educational Resources
No abstract provided.
Smart Contract Development: Challenges And Opportunities, Weiqin Zou, David Lo, Pavneet Singh Kochhar, Xuan-Bach D. Le, Xin Xia, Yang Feng, Zhenyu Chen, Baowen Xu
Smart Contract Development: Challenges And Opportunities, Weiqin Zou, David Lo, Pavneet Singh Kochhar, Xuan-Bach D. Le, Xin Xia, Yang Feng, Zhenyu Chen, Baowen Xu
Research Collection School Of Computing and Information Systems
Smart contract, a term which was originally coined to refer to the automation of legal contracts in general, has recently seen much interest due to the advent of blockchain technology. Recently, the term is popularly used to refer to low-level code scripts running on a blockchain platform. Our study focuses exclusively on this subset of smart contracts. Such smart contracts have increasingly been gaining ground, finding numerous important applications (e.g., crowdfunding) in the real world. Despite the increasing popularity, smart contract development still remains somewhat a mystery to many developers largely due to its special design and applications. Are there …
Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group, Yating Lin, Kamkwai Wong, Yong Wang, Rong Zhang, Bo Dong, Huamin Qu, Qinghua Zheng
Taxthemis: Interactive Mining And Exploration Of Suspicious Tax Evasion Group, Yating Lin, Kamkwai Wong, Yong Wang, Rong Zhang, Bo Dong, Huamin Qu, Qinghua Zheng
Research Collection School Of Computing and Information Systems
Tax evasion is a serious economic problem for many countries, as it can undermine the government’s tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related data. A …
Route Tapestries: Navigating 360° Virtual Tour Videos Using Slit-Scan Visualizations, Jiannan Li, Jiahe Lyu, Maurício Sousa, Ravin Balakrishnan, Anthony Tang, Tovi Grossman
Route Tapestries: Navigating 360° Virtual Tour Videos Using Slit-Scan Visualizations, Jiannan Li, Jiahe Lyu, Maurício Sousa, Ravin Balakrishnan, Anthony Tang, Tovi Grossman
Research Collection School Of Computing and Information Systems
An increasingly popular way of experiencing remote places is by viewing 360° virtual tour videos, which show the surrounding view while traveling through an environment. However, finding particular locations in these videos can be difficult because current interfaces rely on distorted frame previews for navigation. To alleviate this usability issue, we propose Route Tapestries, continuous orthographic-perspective projection of scenes along camera routes. We first introduce an algorithm for automatically constructing Route Tapestries from a 360° video, inspired by the slit-scan photography technique. We then present a desktop video player interface using a Route Tapestry timeline for navigation. An online evaluation …
Holoboard: A Large-Format Immersive Teaching Board Based On Pseudo Holographics, Jiangtao Gong, Teng Han, Siling Guo, Jiannan Li, Siyu Zha, Liuxin Zhang, Feng Tian, Qianying Wang, Yong Rui
Holoboard: A Large-Format Immersive Teaching Board Based On Pseudo Holographics, Jiangtao Gong, Teng Han, Siling Guo, Jiannan Li, Siyu Zha, Liuxin Zhang, Feng Tian, Qianying Wang, Yong Rui
Research Collection School Of Computing and Information Systems
In this paper, we present HoloBoard, an interactive large-format pseduo-holographic display system for lecture based classes. With its unique properties of immersive visual display and transparent screen, we designed and implemented a rich set of novel interaction techniques like immersive presentation, role-play, and lecturing behind the scene that are potentially valuable for lecturing in class. We conducted a controlled experimental study to compare a HoloBoard class with a normal class through measuring students’ learning outcomes and three dimensions of engagement (i.e., behavioral, emotional, and cognitive engagement). We used pre-/post- knowledge tests and multimodal learning analytics to measure students’ learning outcomes …
Uncovering Patterns In Reviewers' Feedback To Scene Description Authors, Rosiana Natalie, Jolene Kar Inn Loh, Huei Suen Tan, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara
Uncovering Patterns In Reviewers' Feedback To Scene Description Authors, Rosiana Natalie, Jolene Kar Inn Loh, Huei Suen Tan, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara
Research Collection School Of Computing and Information Systems
Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1,120 comments that 40 sighted novices received from a sighted or a blind reviewer. We find that feedback patterns tend to fall under four themes: (i) Quality; commenting on different AD quality variables, (ii) Speech Act; the utterance or …
From Continuity To Editability: Inverting Gans With Consecutive Images, Yangyang Xu, Yong Du, Wenpeng Xiao, Xuemiao Xu, Shengfeng He
From Continuity To Editability: Inverting Gans With Consecutive Images, Yangyang Xu, Yong Du, Wenpeng Xiao, Xuemiao Xu, Shengfeng He
Research Collection School Of Computing and Information Systems
Existing GAN inversion methods are stuck in a paradox that the inverted codes can either achieve high-fidelity reconstruction, or retain the editing capability. Having only one of them clearly cannot realize real image editing. In this paper, we resolve this paradox by introducing consecutive images (e.g., video frames or the same person with different poses) into the inversion process. The rationale behind our solution is that the continuity of consecutive images leads to inherent editable directions. This inborn property is used for two unique purposes: 1) regularizing the joint inversion process, such that each of the inverted codes is semantically …
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Burst-Induced Multi-Armed Bandit For Learning Recommendation, Rodrigo Alves, Antoine Ledent, Marius Kloft
Research Collection School Of Computing and Information Systems
In this paper, we introduce a non-stationary and context-free Multi-Armed Bandit (MAB) problem and a novel algorithm (which we refer to as BMAB) to solve it. The problem is context-free in the sense that no side information about users or items is needed. We work in a continuous-time setting where each timestamp corresponds to a visit by a user and a corresponding decision regarding recommendation. The main novelty is that we model the reward distribution as a consequence of variations in the intensity of the activity, and thereby we assist the exploration/exploitation dilemma by exploring the temporal dynamics of the …
Missing Data Imputation For Solar Yield Prediction Using Temporal Multi-Modal Variational Auto-Encoder, Meng Shen, Huaizheng Zhang, Yixin Cao, Fan Yang, Yonggang Wen
Missing Data Imputation For Solar Yield Prediction Using Temporal Multi-Modal Variational Auto-Encoder, Meng Shen, Huaizheng Zhang, Yixin Cao, Fan Yang, Yonggang Wen
Research Collection School Of Computing and Information Systems
The accurate and robust prediction of short-term solar power generation is significant for the management of modern smart grids, where solar power has become a major energy source due to its green and economical nature. However, the solar yield prediction can be difficult to conduct in the real world where hardware and network issues can make the sensors unreachable. Such data missing problem is so prevalent that it degrades the performance of deployed prediction models and even fails the model execution. In this paper, we propose a novel temporal multi-modal variational auto-encoder (TMMVAE) model, to enhance the robustness of short-term …
Privacy-Preserving Voluntary-Tallying Leader Election For Internet Of Things, Tong Wu, Guomin Yang, Liehuang Zhu, Yulin Wu
Privacy-Preserving Voluntary-Tallying Leader Election For Internet Of Things, Tong Wu, Guomin Yang, Liehuang Zhu, Yulin Wu
Research Collection School Of Computing and Information Systems
The Internet of Things (IoT) is commonly deployed with devices of limited power and computation capability. A centralized IoT architecture provides a simplified management for IoT system but brings redundancy by the unnecessary data traffic with a data center. A decentralized IoT reduces the cost on data traffic and is resilient to the single-point-of failure. The blockchain technique has attracted a large amount of research, which is redeemed as a perspective of decentralized IoT system infrastructure. It also brings new privacy challenges for that the blockchain is a public ledger of all digital events executed and shared among all participants. …
Disentangling Hate In Online Memes, Ka Wei, Roy Lee, Rui Cao, Ziqing Fan, Jing Jiang, Wen Haw Chong
Disentangling Hate In Online Memes, Ka Wei, Roy Lee, Rui Cao, Ziqing Fan, Jing Jiang, Wen Haw Chong
Research Collection School Of Computing and Information Systems
Hateful and offensive content detection has been extensively explored in a single modality such as text. However, such toxic information could also be communicated via multimodal content such as online memes. Therefore, detecting multimodal hateful content has recently garnered much attention in academic and industry research communities. This paper aims to contribute to this emerging research topic by proposing DisMultiHate, which is a novel framework that performed the classification of multimodal hateful content. Specifically, DisMultiHate is designed to disentangle target entities in multimodal memes to improve the hateful content classification and explainability. We conduct extensive experiments on two publicly available …
Multi-Modal Recommender Systems: Hands-On Exploration, Quoc Tuan Truong, Aghiles Salah, Hady W. Lauw
Multi-Modal Recommender Systems: Hands-On Exploration, Quoc Tuan Truong, Aghiles Salah, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Recommender systems typically learn from user-item preference data such as ratings and clicks. This information is sparse in nature, i.e., observed user-item preferences often represent less than 5% of possible interactions. One promising direction to alleviate data sparsity is to leverage auxiliary information that may encode additional clues on how users consume items. Examples of such data (referred to as modalities) are social networks, item’s descriptive text, product images. The objective of this tutorial is to offer a comprehensive review of recent advances to represent, transform and incorporate the different modalities into recommendation models. Moreover, through practical hands-on sessions, we …
Links Do Matter: Understanding The Drivers Of Developer Interactions In Software Ecosystems, Subhajit Datta, Amrita Bhattacharjee, Subhashis Majumder
Links Do Matter: Understanding The Drivers Of Developer Interactions In Software Ecosystems, Subhajit Datta, Amrita Bhattacharjee, Subhashis Majumder
Research Collection School Of Computing and Information Systems
Studies of collaborating individuals engaged in collective enterprises usually focus on the individuals, rather than the links supporting their interaction. Accordingly, large scale software development ecosystems have also been examined primarily in terms of developer engagement. We posit that communication links between developers play a central role in the sustenance and effectiveness of such ecosystems. In this paper, we investigate whether and how developer attributes relate to the importance of the communication channels between them. We present a technique using 2nd order Markov models to extract features of interest of the links and apply the technique on data from a …
Multi-Modal Recommender Systems: Hands-On Exploration, Quoc Tuan Truong, Aghiles Salah, Hady Wirawan Lauw
Multi-Modal Recommender Systems: Hands-On Exploration, Quoc Tuan Truong, Aghiles Salah, Hady Wirawan Lauw
Research Collection School Of Computing and Information Systems
Recommender systems typically learn from user-item preference data such as ratings and clicks. This information is sparse in nature, i.e., observed user-item preferences often represent less than 5% of possible interactions. One promising direction to alleviate data sparsity is to leverage auxiliary information that may encode additional clues on how users consume items. Examples of such data (referred to as modalities) are social networks, item’s descriptive text, product images. The objective of this tutorial is to offer a comprehensive review of recent advances to represent, transform and incorporate the different modalities into recommendation models. Moreover, through practical hands-on sessions, we …
On The Usability (In)Security Of In-App Browsing Interfaces In Mobile Apps, Zicheng Zhang, Daoyuan Wu, Lixiang Li, Debin Gao
On The Usability (In)Security Of In-App Browsing Interfaces In Mobile Apps, Zicheng Zhang, Daoyuan Wu, Lixiang Li, Debin Gao
Research Collection School Of Computing and Information Systems
Due to the frequent encountering of web URLs in various application scenarios (e.g., chatting and email reading), many mobile apps build their in-app browsing interfaces (IABIs) to provide a seamless user experience. Although this achieves user-friendliness by avoiding the constant switching between the subject app and the system built-in browser apps, we find that IABIs, if not well designed or customized, could result in usability security risks. In this paper, we conduct the first empirical study on the usability (in)security of in-app browsing interfaces in both Android and iOS apps. Specifically, we collect a dataset of 25 high-profile mobile apps …
Target-Guided Emotion-Aware Chat Machine, Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu, Shanshan Feng
Target-Guided Emotion-Aware Chat Machine, Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu, Shanshan Feng
Research Collection School Of Computing and Information Systems
The consistency of a response to a given post at the semantic level and emotional level is essential for a dialogue system to deliver humanlike interactions. However, this challenge is not well addressed in the literature, since most of the approaches neglect the emotional information conveyed by a post while generating responses. This article addresses this problem and proposes a unified end-to-end neural architecture, which is capable of simultaneously encoding the semantics and the emotions in a post and leveraging target information to generate more intelligent responses with appropriately expressed emotions. Extensive experiments on real-world data demonstrate that the proposed …
Revocable Policy-Based Chameleon Hash, Shengmin Xu, Jianting Ning, Jinhua Ma, Guowen Xu, Jiaming Yuan, Robert H. Deng
Revocable Policy-Based Chameleon Hash, Shengmin Xu, Jianting Ning, Jinhua Ma, Guowen Xu, Jiaming Yuan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Policy-based chameleon hash (PCH) is a cryptographic building block which finds increasing practical applications. Given a message and an access policy, for any chameleon hash generated by a PCH scheme, a chameleon trapdoor holder whose rewriting privileges satisfy the access policy can amend the underlying message without affecting the hash value. In practice, it is necessary to revoke the rewriting privileges of a trapdoor holder due to various reasons, such as change of positions, compromise of credentials, or malicious behaviours. In this paper, we introduce the notion of revocable PCH (RPCH) and formally define its security. We instantiate a concrete …
Visionary Caption: Improving The Accessibility Of Presentation Slides Through Highlighting Visualization, Carmen Ji Yan Yip, Jie Mi Chong, Sin Yee Kwek, Yong Wang, Kotaro Hara
Visionary Caption: Improving The Accessibility Of Presentation Slides Through Highlighting Visualization, Carmen Ji Yan Yip, Jie Mi Chong, Sin Yee Kwek, Yong Wang, Kotaro Hara
Research Collection School Of Computing and Information Systems
Presentation slides are widely used in occasions such as academic talks and business meetings. Captions placed on slides support deaf and hard of hearing (DHH) people to understand spoken contents, but simultaneously comprehending and associating visual contents on slides and caption text could be challenging. In this paper, we design and develop a visualization technique to highlight and associate chart on a slide and numerical data in caption. We first conduct a small formative study with people with and without hearing impairments to assess the value of the visualization technique using a lo-fidelity video prototype. We then develop Visionary Caption, …
Token Shift Transformer For Video Classification, Zhang Hao, Yanbin. Hao, Chong-Wah Ngo
Token Shift Transformer For Video Classification, Zhang Hao, Yanbin. Hao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Transformer achieves remarkable successes in understanding 1 and 2-dimensional signals (e.g., NLP and Image Content Understanding). As a potential alternative to convolutional neural networks, it shares merits of strong interpretability, high discriminative power on hyper-scale data, and flexibility in processing varying length inputs. However, its encoders naturally contain computational intensive operations such as pair-wise self-attention, incurring heavy computational burden when being applied on the complex 3-dimensional video signals. This paper presents Token Shift Module (i.e., TokShift), a novel, zero-parameter, zero-FLOPs operator, for modeling temporal relations within each transformer encoder. Specifically, the TokShift barely temporally shifts partial [Class] token features back-and-forth …
Visilence: An Interactive Visualization Tool For Error Resilience Analysis, Shaolun Ruan, Yong Wang, Qiang Guan
Visilence: An Interactive Visualization Tool For Error Resilience Analysis, Shaolun Ruan, Yong Wang, Qiang Guan
Research Collection School Of Computing and Information Systems
Soft errors have become one of the major concerns for HPC applications, as those errors can result in seriously corrupted outcomes, such as silent data corruptions (SDCs). Prior studies on error resilience have studied the robustness of HPC applications. However, it is still difficult for program developers to identify potential vulnerability to soft errors. In this paper, we present Visilence, a novel visualization tool to visually analyze error vulnerability based on the control-flow graph generated from HPC applications. Visilence efficiently visualizes the affected program states under injected errors and presents the visual analysis of the most vulnerable parts of an …
Design And Supervision Model Of Group Projects For Active Learning, Yi Meng Lau, Kyong Jin Shim, Swapna Gottipati
Design And Supervision Model Of Group Projects For Active Learning, Yi Meng Lau, Kyong Jin Shim, Swapna Gottipati
Research Collection School Of Computing and Information Systems
This research paper presents a group project framework for a second-year programming course, which was conducted during the COVID-19 pandemic. The framework offers well defined stages of the group project which allow students to work on their choice of a real-world problem, integrate their learnings from previous courses, and present a working solution. In the group project, students actively participate, reflect, and contribute to achieving the goals set in the learning objectives of the course. Our framework incorporates key features from Kolb’s Experiential Learning Theory (1984) and principles of active learning from Barnes (1989) to achieve active and experiential learning …
Condensing A Sequence To One Informative Frame For Video Recognition, Qiu. Zhaofan, Ting Yao, Yan Shu, Chong-Wah Ngo, Tao Mei
Condensing A Sequence To One Informative Frame For Video Recognition, Qiu. Zhaofan, Ting Yao, Yan Shu, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
Video is complex due to large variations in motion and rich content in fine-grained visual details. Abstracting useful information from such information-intensive media requires exhaustive computing resources. This paper studies a two-step alternative that first condenses the video sequence to an informative" frame" and then exploits off-the-shelf image recognition system on the synthetic frame. A valid question is how to define" useful information" and then distill it from a video sequence down to one synthetic frame. This paper presents a novel Informative Frame Synthesis (IFS) architecture that incorporates three objective tasks, ie, appearance reconstruction, video categorization, motion estimation, and two …
A First Look At Accessibility Issues In Popular Github Projects, Tingting Bi, Xin Xia, David Lo, Aldeida Aleti
A First Look At Accessibility Issues In Popular Github Projects, Tingting Bi, Xin Xia, David Lo, Aldeida Aleti
Research Collection School Of Computing and Information Systems
Accessibility design elements allow people to access software products and services independent of their different abilities. However, accessibility is challenging to handle and whether accessibility is widely considered in software projects is unclear. In this work, we aim to understand if accessibility is a prevalent consideration in practice, what accessibility issues are discussed in GitHub projects, what potential reasons cause accessibility issues, and what solutions (e.g., tools and standards) are applied for addressing accessibility issues. In this work, we collect 11,820 accessibility issues and their threads discussed by developers in popular GitHub projects. We manually analyzed and grouped the collected …
Deep Learning For Image Super-Resolution: A Survey, Zhihao Wang, Jian Chen, Steven C. H. Hoi
Deep Learning For Image Super-Resolution: A Survey, Zhihao Wang, Jian Chen, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning techniques. This article aims to provide a comprehensive survey on recent advances of image super-resolution using deep learning approaches. In general, we can roughly group the existing studies of SR techniques into three major categories: supervised SR, unsupervised SR, and domain-specific SR. In addition, we also cover some other important issues, such as publicly available benchmark datasets and performance evaluation metrics. Finally, we conclude this survey by …
Online Learning: A Comprehensive Survey, Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao
Online Learning: A Comprehensive Survey, Steven C. H. Hoi, Doyen Sahoo, Jing Lu, Peilin Zhao
Research Collection School Of Computing and Information Systems
Online learning represents a family of machine learning methods, where a learner attempts to tackle some predictive (or any type of decision-making) task by learning from a sequence of data instances one by one at each time. The goal of online learning is to maximize the accuracy/correctness for the sequence of predictions/decisions made by the online learner given the knowledge of correct answers to previous prediction/learning tasks and possibly additional information. This is in contrast to traditional batch or offline machine learning methods that are often designed to learn a model from the entire training data set at once. Online …
Eargate: Gait-Based User Identification With In-Ear Microphones, Andrea Ferlini, Dong Ma, Cecilia Mascolo
Eargate: Gait-Based User Identification With In-Ear Microphones, Andrea Ferlini, Dong Ma, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
Human gait is a widely used biometric trait for user identification and recognition. Given the wide-spreading, steady diffusion of earworn wearables (Earables) as the new frontier of wearable devices, we investigate the feasibility of earable-based gait identification. Specifically, we look at gait-based identification from the sounds induced by walking and propagated through the musculoskeletal system in the body. Our system, EarGate, leverages an in-ear facing microphone which exploits the earable’s occlusion effect to reliably detect the user’s gait from inside the ear canal, without impairing the general usage of earphones. With data collected from 31 subjects, we show that EarGate …
Solarslam: Battery-Free Loop Closure For Indoor Localisation, Bo Wei, Weitao Xu, Chengwen Luo, Guillaume Zoppi, Dong Ma, Sen Wang
Solarslam: Battery-Free Loop Closure For Indoor Localisation, Bo Wei, Weitao Xu, Chengwen Luo, Guillaume Zoppi, Dong Ma, Sen Wang
Research Collection School Of Computing and Information Systems
In this paper, we propose SolarSLAM, a batteryfree loop closure method for indoor localisation. Inertial Measurement Unit (IMU) based indoor localisation method has been widely used due to its ubiquity in mobile devices, such as mobile phones, smartwatches and wearable bands. However, it suffers from the unavoidable long term drift. To mitigate the localisation error, many loop closure solutions have been proposed using sophisticated sensors, such as cameras, laser, etc. Despite achieving high-precision localisation performance, these sensors consume a huge amount of energy. Different from those solutions, the proposed SolarSLAM takes advantage of an energy harvesting solar cell as a …