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Articles 61 - 90 of 135
Full-Text Articles in Graphics and Human Computer Interfaces
Cookgan: Causality Based Text-To-Image Synthesis, Bin Zhu, Chong-Wah Ngo
Cookgan: Causality Based Text-To-Image Synthesis, Bin Zhu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper addresses the problem of text-to-image synthesis from a new perspective, i.e., the cause-and-effect chain in image generation. Causality is a common phenomenon in cooking. The dish appearance changes depending on the cooking actions and ingredients. The challenge of synthesis is that a generated image should depict the visual result of action-on-object. This paper presents a new network architecture, CookGAN, that mimics visual effect in causality chain, preserves fine-grained details and progressively upsamples image. Particularly, a cooking simulator sub-network is proposed to incrementally make changes to food images based on the interaction between ingredients and cooking methods over a …
Mnemonics Training: Multi-Class Incremental Learning Without Forgetting, Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun
Mnemonics Training: Multi-Class Incremental Learning Without Forgetting, Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun
Research Collection School Of Computing and Information Systems
Multi-Class Incremental Learning (MCIL) aims to learn new concepts by incrementally updating a model trained on previous concepts. However, there is an inherent trade-off to effectively learning new concepts without catastrophic forgetting of previous ones. To alleviate this issue, it has been proposed to keep around a few examples of the previous concepts but the effectiveness of this approach heavily depends on the representativeness of these examples. This paper proposes a novel and automatic framework we call mnemonics, where we parameterize exemplars and make them optimizable in an end-to-end manner. We train the framework through bilevel optimizations, i.e., model-level and …
Don't Hit Me! Glass Detection In Real-World Scenes, Haiyang Mei, Xin Yang, Yang Wang, Yuanyuan Liu, Shengfeng He, Qiang Zhang, Xiaopeng Wei, Rynson W.H. Lau
Don't Hit Me! Glass Detection In Real-World Scenes, Haiyang Mei, Xin Yang, Yang Wang, Yuanyuan Liu, Shengfeng He, Qiang Zhang, Xiaopeng Wei, Rynson W.H. Lau
Research Collection School Of Computing and Information Systems
Glass is very common in our daily life. Existing computer vision systems neglect it and thus may have severe consequences, e.g., a robot may crash into a glass wall. However, sensing the presence of glass is not straightforward. The key challenge is that arbitrary objects/scenes can appear behind the glass, and the content within the glass region is typically similar to those behind it. In this paper, we propose an important problem of detecting glass from a single RGB image. To address this problem, we construct a large-scale glass detection dataset (GDD) and design a glass detection network, called GDNet, …
Hyperbolic Visual Embedding Learning For Zero-Shot Recognition, Shaoteng Liu, Jingjing Chen, Liangming Pan, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang
Hyperbolic Visual Embedding Learning For Zero-Shot Recognition, Shaoteng Liu, Jingjing Chen, Liangming Pan, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang
Research Collection School Of Computing and Information Systems
This paper proposes a Hyperbolic Visual Embedding Learning Network for zero-shot recognition. The network learns image embeddings in hyperbolic space, which is capable of preserving the hierarchical structure of semantic classes in low dimensions. Comparing with existing zeroshot learning approaches, the network is more robust because the embedding feature in hyperbolic space better represents class hierarchy and thereby avoid misleading resulted from unrelated siblings. Our network outperforms exiting baselines under hierarchical evaluation with an extremely challenging setting, i.e., learning only from 1,000 categories to recognize 20,841 unseen categories. While under flat evaluation, it has competitive performance as state-of-the-art methods but …
Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
Research Collection School Of Computing and Information Systems
Semantic segmentation often requires a large set of images with pixel-level annotations. In the view of extremely expensive expert labeling, recent research has shown that the models trained on photo-realistic synthetic data (e.g., computer games) with computer-generated annotations can be adapted to real images. Despite this progress, without constraining the prediction on real images, the models will easily overfit on synthetic data due to severe domain mismatch. In this paper, we novelly exploit the intrinsic properties of semantic segmentation to alleviate such problem for model transfer. Specifically, we present a Regularizer of Prediction Transfer (RPT) that imposes the intrinsic properties …
Exploring Category-Agnostic Clusters For Open-Set Domain Adaptation, Yingwei Pan, Ting Yao, Yehao Li, Chong-Wah Ngo, Tao Mei
Exploring Category-Agnostic Clusters For Open-Set Domain Adaptation, Yingwei Pan, Ting Yao, Yehao Li, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
Unsupervised domain adaptation has received significant attention in recent years. Most of existing works tackle the closed-set scenario, assuming that the source and target domains share the exactly same categories. In practice, nevertheless, a target domain often contains samples of classes unseen in source domain (i.e., unknown class). The extension of domain adaptation from closedset to such open-set situation is not trivial since the target samples in unknown class are not expected to align with the source. In this paper, we address this problem by augmenting the state-of-the-art domain adaptation technique, Self-Ensembling, with category-agnostic clusters in target domain. Specifically, we …
Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA. Given a set of detected object regions in an image (e.g., using Faster R-CNN), like any other unsupervised feature learning methods (e.g., word2vec), the proxy training objective of VC R-CNN is to predict the contextual objects of a region. However, they are fundamentally different: the prediction of VC R-CNN is by using causal intervention: P(Y|do(X)), while others are by using the conventional likelihood: P(Y|X). This is also …
Visual Commonsense Representation Learning Via Causal Inference, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Visual Commonsense Representation Learning Via Causal Inference, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA. Given a set of detected object regions in an image (e.g., using Faster R-CNN), like any other unsupervised feature learning methods (e.g., word2vec), the proxy training objective of VC R-CNN is to predict the con-textual objects of a region. However, they are fundamentally different: the prediction of VC R-CNN is by using causal intervention: P(Y|do(X)), while others are by using the conventional likelihood: P(Y|X). We extensively apply …
Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei
Design And Test Of An Autonomy Monitoring Service To Detect Divergent Behaviors On Unmanned Aerial Systems, Loay Y. Almannaei
Theses and Dissertations
Operation of Unmanned Aerial Vehicles (UAV) support many critical missions in the United State Air Force (USAF). Monitoring abnormal behavior is one of many responsibilities of the operator during a mission. Some behaviors are hard to be detect by an operator, especially when flying one or more autonomous vehicles; as such, detections require a high level of attention and focus to flight parameters. In this research, a monitoring system and its algorithm are designed and tested for a target fixed-wing UAV. The Autonomy Monitoring Service (AMS) compares the real vehicle or simulated Vehicle with a similar simulated vehicle using Software …
Video Synthesis From The Stylegan Latent Space, Lei Zhang
Video Synthesis From The Stylegan Latent Space, Lei Zhang
Master's Projects
Generative models have shown impressive results in generating synthetic images. However, video synthesis is still difficult to achieve, even for these generative models. The best videos that generative models can currently create are a few seconds long, distorted, and low resolution. For this project, I propose and implement a model to synthesize videos at 1024x1024x32 resolution that include human facial expressions by using static images generated from a Generative Adversarial Network trained on the human facial images. To the best of my knowledge, this is the first work that generates realistic videos that are larger than 256x256 resolution from single …
Graphical Representation Of Text Semantics, Karl Kevin Tiba Fossoh
Graphical Representation Of Text Semantics, Karl Kevin Tiba Fossoh
Master of Science in Computer Science Theses
A text is a set of words conveying a particular semantic based on their order, representation and structure. Those elements can be associated through a different set of interpretations, based on frequency and proportionality. The problem with context is that numbers do not help understand the semantics and fall short to convey the message of the text. The graphical representation of text semantics focuses on the conversion of text to images. Contrarily to word clouds that simply produce frequency mapping of words within the text and topic models that essentially give context to word frequencies and proportionalities, images keep intact …
Exploring Attacks And Defenses In Additive Manufacturing Processes: Implications In Cyber-Physical Security, Nicholas Deily
Exploring Attacks And Defenses In Additive Manufacturing Processes: Implications In Cyber-Physical Security, Nicholas Deily
McKelvey School of Engineering Graduate Student Theses & Dissertations
Many industries are rapidly adopting additive manufacturing (AM) because of the added versatility this technology offers over traditional manufacturing techniques. But with AM, there comes a unique set of security challenges that must be addressed. In particular, the issue of part verification is critically important given the growing reliance of safety-critical systems on 3D printed parts. In this thesis, the current state of part verification technologies will be examined in the con- text of AM-specific geometric-modification attacks, and an automated tool for 3D printed part verification will be presented. This work will cover: 1) the impacts of malicious attacks on …
Exploring Usage Of Web Resources Through A Model Of Api Learning, Finn Voichick
Exploring Usage Of Web Resources Through A Model Of Api Learning, Finn Voichick
McKelvey School of Engineering Graduate Student Theses & Dissertations
Application programming interfaces (APIs) are essential to modern software development, and new APIs are frequently being produced. Consequently, software developers must regularly learn new APIs, which they typically do on the job from online resources rather than in a formal educational context. The Kelleher–Ichinco COIL model, an acronym for “Collection and Organization of Information for Learning,” was recently developed to model the entire API learning process, drawing from information foraging theory, cognitive load theory, and external memory research. We ran an exploratory empirical user study in which participants performed a programming task using the React API with the goal of …
Voxel Optimization, Scott Bengs
Voxel Optimization, Scott Bengs
Student Academic Conference
Voxel Optimization This poster presentation covers optimization for voxels. They can be thought of as three dimensional pixels. Vo coming from volume and xel from pixel. Voxels are just values placed in a 3D grid. Voxels have many interesting uses in the medical and scientific field, especially in geology. One use in computer science is storing world information for video games or graphical applications. One very popular example is Minecraft, a game that allows all of the world to be changed, that uses cube shaped voxels. The first topic will be on the naive approach of building a model from …
Server Score, Zachary Buresh
Server Score, Zachary Buresh
Student Academic Conference
This presentation is in regards to the Android mobile application that I developed in the Kotlin programming language named "Server Score". The app helps waiters/waitresses calculate, track, and predict performance related statistics on the job.
User Experience As A Rhetorical Medium: User At The Intersection Of Audience, Reader And Actor, Áine Doyle
User Experience As A Rhetorical Medium: User At The Intersection Of Audience, Reader And Actor, Áine Doyle
English Honors Theses
The goal of this project is to demonstrate how digital interfaces are bodies of visual language that can be “close-read” and interpreted critically, just like any other traditional text; digital user interfaces, like poetry and novels, have form and content that complement and shape the meaning and interpretation of the other. It is meant to encourage academic discussions about digital interfaces to go beyond whether social media is “good” or “bad” to how digital interfaces are structured, why they are structured the way they are, and what effects these structures have on the way they communicate information and content to …
Generating Acoustic Projections Using 3d Models, Jake A. Brazelton
Generating Acoustic Projections Using 3d Models, Jake A. Brazelton
Senior Honors Projects, 2020-current
Raytracing is used in commercial graphics engines most commonly for lighting effects, but it also has many uses when it comes to acoustic simulation. Adopted directly from these computer graphics programs, the formulas presented herein enable the visualization of acoustic intensity levels throughout a 3D space using Python 3 and the OpenGL library. In addition to visualization, they also provide the ability to calculate the reverberation time and critical distance of an enclosed space in relation to its size and material makeup. The described application bundles all of these components together in a Qt5 application that allows users to view …
Investigating Machine Learning Techniques For Gesture Recognition With Low-Cost Capacitive Sensing Arrays, Michael Fahr Jr.
Investigating Machine Learning Techniques For Gesture Recognition With Low-Cost Capacitive Sensing Arrays, Michael Fahr Jr.
Computer Science and Computer Engineering Undergraduate Honors Theses
Machine learning has proven to be an effective tool for forming models to make predictions based on sample data. Supervised learning, a subset of machine learning, can be used to map input data to output labels based on pre-existing paired data. Datasets for machine learning can be created from many different sources and vary in complexity, with popular datasets including the MNIST handwritten dataset and CIFAR10 image dataset. The focus of this thesis is to test and validate multiple machine learning models for accurately classifying gestures performed on a low-cost capacitive sensing array. Multiple neural networks are trained using gesture …
Speech Processing In Computer Vision Applications, Nicholas Waterworth
Speech Processing In Computer Vision Applications, Nicholas Waterworth
Computer Science and Computer Engineering Undergraduate Honors Theses
Deep learning has been recently proven to be a viable asset in determining features in the field of Speech Analysis. Deep learning methods like Convolutional Neural Networks facilitate the expansion of specific feature information in waveforms, allowing networks to create more feature dense representations of data. Our work attempts to address the problem of re-creating a face given a speaker's voice and speaker identification using deep learning methods. In this work, we first review the fundamental background in speech processing and its related applications. Then we introduce novel deep learning-based methods to speech feature analysis. Finally, we will present our …
Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean
Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean
Computational and Data Sciences (PhD) Dissertations
"Social communication is the use of language in social contexts. It encompasses social interaction, social cognition, pragmatics, and language processing” [3]. One presumed prerequisite of social communication is visual attention–the focus of this work. “Visual attention is a process that directs a tiny fraction of the information arriving at primary visual cortex to high-level centers involved in visual working memory and pattern recognition” [7]. This process involves the integration of two streams: the global and local streams; the global stream rapidly processes the scene, and the local stream processes details. This integration is important to social communication in that attending …
Tidytouch: An Interactive Visualization Tool For Data Science Education, Jonah E. Devaney
Tidytouch: An Interactive Visualization Tool For Data Science Education, Jonah E. Devaney
Undergraduate Honors Theses
Accessibility and usability of software define the programs used for both professional and academic activities. While many proprietary tools are easy to grasp, some challenges exist in using more technical resources, such as the statistical programming language R. The creative project tidyTouch is a web application designed to help educate any user in basic R data visualization and transformation using the popular ggplot2 and dplyr packages. Providing point-and-click interactivity to explore potential modifications of graphics for data presentation, the application uses an intuitive interface to make R more accessible to those without programming experience. This project is in a state …
Stay-At-Home Motor Rehabilitation: Optimizing Spatiotemporal Learning On Low-Cost Capacitive Sensor Arrays, Reid Sutherland
Stay-At-Home Motor Rehabilitation: Optimizing Spatiotemporal Learning On Low-Cost Capacitive Sensor Arrays, Reid Sutherland
Graduate Theses and Dissertations
Repeated, consistent, and precise gesture performance is a key part of recovery for stroke and other motor-impaired patients. Close professional supervision to these exercises is also essential to ensure proper neuromotor repair, which consumes a large amount of medical resources. Gesture recognition systems are emerging as stay-at-home solutions to this problem, but the best solutions are expensive, and the inexpensive solutions are not universal enough to tackle patient-to-patient variability. While many methods have been studied and implemented, the gesture recognition system designer does not have a strategy to effectively predict the right method to fit the needs of a patient. …
Starhopper: A Touch Interface For Remote Object-Centric Drone Navigation, Jiannan Li, Ravin Balakrishnan, Tovi Grossman
Starhopper: A Touch Interface For Remote Object-Centric Drone Navigation, Jiannan Li, Ravin Balakrishnan, Tovi Grossman
Research Collection School Of Computing and Information Systems
Camera drones, a rapidly emerging technology, offer people the ability to remotely inspect an environment with a high degree of mobility and agility. However, manual remote piloting of a drone is prone to errors. In contrast, autopilot systems can require a significant degree of environmental knowledge and are not necessarily designed to support flexible visual inspections. Inspired by camera manipulation techniques in interactive graphics, we designed StarHopper, a novel touch screen interface for efficient object-centric camera drone navigation, in which a user directly specifies the navigation of a drone camera relative to a specified object of interest. The system relies …
Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan
Use Of Eye-Tracking To Identify Psychological Indicators Of Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah, Matthew Thimgan
Research Collection School Of Computing and Information Systems
Sleepiness or sleep deprivation creates a serious hazard or obstacle to task execution and performance. Sleep deprivation can be life-threating (e.g., when driving or executing attention-critical tasks). We are interested to examine if eye-tracking technology can be used to assess and detect sleepiness in an online environment. In this research proposal, we will focus on examining the relationships between sleepiness and parameters involving pupil size, blinks, and saccades.
Assistance For Target Selection In Mobile Augmented Reality, Vinod Asokan, Scott Bateman, Anthony Tang
Assistance For Target Selection In Mobile Augmented Reality, Vinod Asokan, Scott Bateman, Anthony Tang
Research Collection School Of Computing and Information Systems
Mobile augmented reality - where a mobile device is used to view and interact with virtual objects displayed in the real world - is becoming more common. Target selection is the main method of interaction in mobile AR, but is particularly difficult because targets in AR can have challenging characteristics such as being moving or occluded (by digital or real world objects). Because target selection is particularly difficult and error prone in mobile AR, we conduct a comparative study of target assistance techniques. We compared four different cursor-based selection techniques against the standard touch-to-select interaction, finding that a newly adapted …
Relationships Between Willingness To Share Information For Benefits And Trust, Gaurav Bansal, Fiona Fui-Hoon Nah
Relationships Between Willingness To Share Information For Benefits And Trust, Gaurav Bansal, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
This research examines the role of willingness to share one’s information for three benefits as tradeoffs – monetary gains, personalization, and national security – and their effects on trust in online businesses. Data were gathered from MTurk and the results indicate that willingness to share information for monetary gains and personalization is marginally associated with trust in online businesses, but willingness to share information for national security has no association with trust in online businesses. The paper also discusses implications, limitations, and future research directions.
Storage Management Strategy In Mobile Phones For Photo Crowdsensing, En Wang, Zhengdao Qu, Xinyao Liang, Xiangyu Meng, Yongjian Yang, Dawei Li, Weibin Meng
Storage Management Strategy In Mobile Phones For Photo Crowdsensing, En Wang, Zhengdao Qu, Xinyao Liang, Xiangyu Meng, Yongjian Yang, Dawei Li, Weibin Meng
Department of Computer Science Faculty Scholarship and Creative Works
In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to …
A Distributed Model-View-Controller Design Pattern For A Graphical Remote Control Of A Multi-User Application, Dale E. Parson
A Distributed Model-View-Controller Design Pattern For A Graphical Remote Control Of A Multi-User Application, Dale E. Parson
Computer Science and Information Technology Faculty
The Model-View-Controller (MVC) is a design pattern for architecting the interactions among human users of graphical computing systems with the software Controller that manages user input, the Model that houses system state, and the View that projects the Model state into intelligible graphical form. The present work examines extending MVC into a Distributed Model-View-Controller pattern, starting with a stand-alone MVC system that is amenable to distribution over a local area network (LAN). Distribution takes the form of cloning a stand-alone MVC application into distinct client and server programs, and then altering each for its purpose while maintaining the initial graphical …
The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Adam Kern
The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Adam Kern
McKelvey School of Engineering Graduate Student Theses & Dissertations
The main purpose of information visualization is to act as a window between a user and data. Historically, this has been accomplished via a single-agent framework: the only decisionmaker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but from necessity: prior to this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This thesis aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …
Dfseer: A Visual Analytics Approach To Facilitate Model Selection For Demand Forecasting, Dong Sun, Zezheng Feng, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu
Dfseer: A Visual Analytics Approach To Facilitate Model Selection For Demand Forecasting, Dong Sun, Zezheng Feng, Yuanzhe Chen, Yong Wang, Jia Zeng, Mingxuan Yuan, Ting-Chuen Pong, Huamin Qu
Research Collection School Of Computing and Information Systems
Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users’ demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model …