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Graphics and Human Computer Interfaces Commons™

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2020

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Articles 31 - 60 of 136

Full-Text Articles in Graphics and Human Computer Interfaces

Visualization Research Lab At Hkust, Yong Wang Sep 2020

Visualization Research Lab At Hkust, Yong Wang

Research Collection School Of Computing and Information Systems

HKUST VisLab (http://vis.cse.ust.hk/) is one of the leading research labs in the field of data visualization and human-computer interaction worldwide. The lab is dedicated to conducting cutting-edge research on data visualization and human-computer interaction to facilitate data exploration and analytics in various application domains, including E-learning, urban computing, social media and industry 4.0. Starting from its foundation by Prof. Huamin Qu in August 2004, the mission of HKUST VisLab is to build an excellent visualization research center and foster data visualization research and talent cultivation in Asia, as there were very few visualization researchers in Asia around 2004.

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Weakly Paired Multi-Domain Image Translation, M.Y. Zhang, Zhiwu Huang, D.P. Paudel, J. Thoma, Gool L. Van Sep 2020

Weakly Paired Multi-Domain Image Translation, M.Y. Zhang, Zhiwu Huang, D.P. Paudel, J. Thoma, Gool L. Van

Research Collection School Of Computing and Information Systems

In this paper, we aim at studying the new problem of weakly paired multi-domain image translation. To this end, we collect a dataset that contains weakly paired images from multiple domains. Two images are considered to be weakly paired if they are captured from nearby locations and share an overlapping field of view. These images are possibly captured by two asynchronous cameras—often resulting in images from separate domains, e.g. summer and winter. Major motivations for using weakly paired images are: (i) performance improvement towards that of paired data; (ii) cheap labels and abundant data availability. For the first time in …

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Comparison Of Machine Learning Models: Gesture Recognition Using A Multimodal Wrist Orthosis For Tetraplegics, Charlie Martin Aug 2020

Comparison Of Machine Learning Models: Gesture Recognition Using A Multimodal Wrist Orthosis For Tetraplegics, Charlie Martin

The Journal of Purdue Undergraduate Research

Many tetraplegics must wear wrist braces to support paralyzed wrists and hands. However, current wrist orthoses have limited functionality to assist a person’s ability to perform typical activities of daily living other than a small pocket to hold utensils. To enhance the functionality of wrist orthoses, gesture recognition technology can be applied to control mechatronic tools attached to a novel fabricated wrist brace. Gesture recognition is a growing technology for providing touchless human-computer interaction that can be particularly useful for tetraplegics with limited upper-extremity mobility. In this study, three gesture recognition models were compared—two dynamic time-warping models and a hidden …

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Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess Aug 2020

Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess

MS in Computer Science Project Reports

OpenCV is a popular tool for developing computer vision algorithms; however, prototyping OpenCV-based algorithms is a time consuming and iterative process. VisualOCV is an open source tool to help users better understand and create computer vision algorithms. A user can see how data is processed at each step in their algorithm, and the results of any changes to the algorithm will be displayed to the user immediately. This can allow the user to easily experiment with various computer vision methods and their parameters. EyeCalc 1.0 uses the Microsoft Foundation Class Library, an old GUI framework by Microsoft, and contains various …

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Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus Aug 2020

Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus

Theses and Dissertations

This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …

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Virtual Reality: A Tool Used To Engage Youth In The Voting Process In Newly Democratic Tunisia, Raed Ghanja Aug 2020

Virtual Reality: A Tool Used To Engage Youth In The Voting Process In Newly Democratic Tunisia, Raed Ghanja

International Programs

Tunisia is facing a hard time with its transition to democracy partly due to the reluctance on the part of young people to participate in elections. This poster discusses why the Tunisian government must engage youth and encourage their participation in the election process by using fun simulations of this process in Virtual Reality.

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Cognition And Context-Aware Computing: Towards A Situation-Aware System With A Case Study In Aviation, Justin C. Wilson Aug 2020

Cognition And Context-Aware Computing: Towards A Situation-Aware System With A Case Study In Aviation, Justin C. Wilson

Computer Science and Engineering Theses and Dissertations

In aviation, flight instructors seek to comprehend the intent and awareness of their students. With this awareness, derived from in-flight observation and post-flight examination, a human instructor can infer the internal contexts of their student aviators as they perform. It is this understanding that is fundamental for evaluating student development. Further, a well-understood construct for describing the state of knowledge about a dynamic environment is known as situational awareness (SA). Often pilot error is associated with SA [80], and it is fundamental to flight safety and mission execution. If these contexts can be automatically inferred, instructors and students can more …

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A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang Aug 2020

A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang

Dissertations

OBJECTIVES. Coronary artery disease (CAD) is the most common type of heart disease and kills over 360,000 people a year in the United States. Myocardial revascularization (MR) is a standard interventional treatment for patients with stable CAD. Fluoroscopy angiography is real-time anatomical imaging and routinely used to guide MR by visually estimating the percent stenosis of coronary arteries. However, a lot of patients do not benefit from the anatomical information-guided MR without functional testing. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a widely used functional testing for CAD evaluation but limits to the absence of anatomical information. …

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Interface Design Of Web-Based Educational Platforms For Young Students, Lurong He, Fiona Fui-Hoon Nah Aug 2020

Interface Design Of Web-Based Educational Platforms For Young Students, Lurong He, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

With the outbreak of the Covid-19 pandemic, almost all the school programs in the United States are closed. Most educational programs have moved online. Both teachers and students are facing challenges adapting to this new teaching and learning mode. This paper will focus on the interface design of webbased educational platforms for students and teachers from elementary and middle schools. The age of students from elementary and middle schools typically ranges from 5 to 13 years old. Their computer literacy level is still preliminary. So traditional online teaching platforms may not be appropriate for them. The design of learning systems …

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Three-Dimensional (3d) Reconstruction Of Ultrasound Foetal Images Using Visualisation Toolkit (Vtk), Henry Dusim Grace Anabela Aug 2020

Three-Dimensional (3d) Reconstruction Of Ultrasound Foetal Images Using Visualisation Toolkit (Vtk), Henry Dusim Grace Anabela

Student Works (2020-2029)

Three-dimensional (3D) reconstruction of two-dimensional (2D) ultrasound images has been used for easier analysing of anatomy related to abnormalities. 3D image reconstruction is required as it helps doctors interpret results and assess any defects quickly. Not only does it improve the accuracy of diagnosis, but it also saves a lot of time. In this thesis, 295 slices of 2D ultrasound images of a foetal are used to do 3D reconstruction using surface rendering, volume rendering, and multiplanar rendering technique. A similar software known as 3D Slicer is also used to reconstruct the ultrasound image for comparison purpose. VTK can easily …

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Mining User-Generated Content Of Mobile Patient Portal: Dimensions Of User Experience, Mohammad A. Al-Ramahi, Cherie Noteboom Aug 2020

Mining User-Generated Content Of Mobile Patient Portal: Dimensions Of User Experience, Mohammad A. Al-Ramahi, Cherie Noteboom

Computer Information Systems Faculty Publications (Archived)

Patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. The incorporation of patient portals provides the promise to deliver excellent quality, at optimized costs, while improving the health of the population. This study extends the existing literature by extracting dimensions related to the Mobile Patient Portal Use. We use a topic modeling approach to systematically analyze users’ feedback from the actual use of a common mobile patient portal, Epic's MyChart. Comparing results of Latent Dirichlet Allocation analysis with those of human analysis validated the extracted …

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Tenet: Triple Excitation Network For Video Salient Object Detection, Sucheng Ren, Chu Han, Xin Yang, Guoqiang Han, Shengfeng He Aug 2020

Tenet: Triple Excitation Network For Video Salient Object Detection, Sucheng Ren, Chu Han, Xin Yang, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

In this paper, we propose a simple yet effective approach, named Triple Excitation Network, to reinforce the training of video salient object detection (VSOD) from three aspects, spatial, temporal, and online excitations. These excitation mechanisms are designed following the spirit of curriculum learning and aim to reduce learning ambiguities at the beginning of training by selectively exciting feature activations using ground truth. Then we gradually reduce the weight of ground truth excitations by a curriculum rate and replace it by a curriculum complementary map for better and faster convergence. In particular, the spatial excitation strengthens feature activations for clear object …

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Virtual Temari: Artistically Inspired Mathematics, Carl Giuffre, Lee Stemkoski Jul 2020

Virtual Temari: Artistically Inspired Mathematics, Carl Giuffre, Lee Stemkoski

Journal of Humanistic Mathematics

Technology can be a significant aide in understanding and appreciating geometry, beyond theoretical considerations. Both fiber art and technology have been employed as a significant aide and an inspiring vessel in education to explore geometry. The Japanese craft known as temari, or "hand-balls", combines important artistic, spiritual, and familial values, and provides one such approach to exploring geometry. Mathematically, the artwork of temari may be classified based on whether they are inspired by polyhedra and discrete patterns or by periodic functional curves. The resulting designs of these categories provide an ancient vantage for displaying spherical patterns. We illustrate a …

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Exploring User Interface Improvements For Software Developers Who Are Blind, Guarionex J. Salivia, Flint D. Million, Megan E. Bening Jul 2020

Exploring User Interface Improvements For Software Developers Who Are Blind, Guarionex J. Salivia, Flint D. Million, Megan E. Bening

Journal of Science Education for Students with Disabilities

Software developers who are blind and interact with the computer non-visually face unique challenges with information retrieval. We explore the use of speech and Braille combined with software to provide an improved interface to aid with challenges associated with information retrieval. We motivate our design on common tasks performed by students in a software development course using a Microprocessor without Interlocked Pipeline Stages (MIPS) architecture simulation tool. We test our interface via a single-subject longitudinal study, and we measure and show improvement in both the user’s performance and the user experience.

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Digital Modeling Of Cultural Heritage Objects, Snehal Padhye, James Ferwerda Jul 2020

Digital Modeling Of Cultural Heritage Objects, Snehal Padhye, James Ferwerda

Frameless

Cultural heritage objects are a rich source of information about human history. Due to the physical nature of these often old and typically rare or unique objects, humanity is at risk of losing this history. Given their importance, preservation is an active area of interest in the research community. While, digitally capturing images of the objects is common practice, we propose a more comprehensive approach to preserving these objects. It involves creating digital models that represent both the three-dimensional shapes of the objects and the materials they are made of.

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Poetry For Seers Or The Peruvian Visual Poetic Tradition In Front Of New Media, Michael Hurtado, Pamela Medina, Enrique García, Michael Prado Jul 2020

Poetry For Seers Or The Peruvian Visual Poetic Tradition In Front Of New Media, Michael Hurtado, Pamela Medina, Enrique García, Michael Prado

Electronic Literature Organization Conference 2020

Since the first decades of the twentieth century, Peruvian poetic tradition has been characterized by experimental uses of language. Among these possibilities, some records tensioned this medium from the link with the plastic arts, as in the case of the poetry of José María Eguren, while others opted for the playing with the spatiality and visuality of the blank sheet, such as in the case of the work of Carlos Oquendo de Amat. However, it is not until the appearance of the poetry of César Vallejo, specifically with a poems like Trilce in 1922, that these breakages force us to …

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The Meaning Of Red And Green In User Interfaces For The Color Deficient, Bassel Hamieh Jul 2020

The Meaning Of Red And Green In User Interfaces For The Color Deficient, Bassel Hamieh

University Honors Theses

Around 108 million web users are color blind which is a problem when the way we communicate over the web or interfaces is through the use of color. Red and green are two colors that are especially heavily used in interface design because of their strong symbolic associations; red being a sign to warn or stop and green being the opposite. This has a large effect on red-green color blind people who are not able to perceive either of those colors correctly. Many solutions exist that aim to help through color differentiation but none take into account color symbolism. With …

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Expertise Style Transfer: A New Task Towards Better Communication Between Experts And Laymen, Yixin Cao, Ruihao Shui, Liangming Pan, Min-Yen Kan, Zhiyuan Lu, Tat-Seng Chua Jul 2020

Expertise Style Transfer: A New Task Towards Better Communication Between Experts And Laymen, Yixin Cao, Ruihao Shui, Liangming Pan, Min-Yen Kan, Zhiyuan Lu, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The curse of knowledge can impede communication between experts and laymen. We propose a new task of expertise style transfer and contribute a manually annotated dataset with the goal of alleviating such cognitive biases. Solving this task not only simplifies the professional language, but also improves the accuracy and expertise level of laymen descriptions using simple words. This is a challenging task, unaddressed in previous work, as it requires the models to have expert intelligence in order to modify text with a deep understanding of domain knowledge and structures. We establish the benchmark performance of five state-of-the-art models for style …

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Tree-Augmented Cross-Modal Encoding For Complex-Query Video Retrieval, Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, Tat-Seng Chua Jul 2020

Tree-Augmented Cross-Modal Encoding For Complex-Query Video Retrieval, Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The rapid growth of user-generated videos on the Internet has intensified the need for text-based video retrieval systems. Traditional methods mainly favor the concept-based paradigm on retrieval with simple queries, which are usually ineffective for complex queries that carry far more complex semantics. Recently, embedding-based paradigm has emerged as a popular approach. It aims to map the queries and videos into a shared embedding space where semantically-similar texts and videos are much closer to each other. Despite its simplicity, it forgoes the exploitation of the syntactic structure of text queries, making it suboptimal to model the complex queries. To facilitate …

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Deep Learning Of Facial Embeddings And Facial Landmark Points For The Detection Of Academic Emotions, Hua Leong Fwa Jul 2020

Deep Learning Of Facial Embeddings And Facial Landmark Points For The Detection Of Academic Emotions, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Automatic emotion recognition is an actively researched area as emotion plays a pivotal role in effective human communications. Equipping a computer to understand and respond to human emotions has potential applications in many fields including education, medicine, transport and hospitality. In a classroom or online learning context, the basic emotions do not occur frequently and do not influence the learning process itself. The academic emotions such as engagement, frustration, confusion and boredom are the ones which are pivotal to sustaining the motivation of learners. In this study, we evaluated the use of deep learning on FaceNet embeddings and facial landmark …

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An Improved Bone Age Assessment Using Advanced Image Processing And Deep Learning Approach, Kim Meng Liang Jul 2020

An Improved Bone Age Assessment Using Advanced Image Processing And Deep Learning Approach, Kim Meng Liang

Student Works (2020-2029)

Pediatricians often apply bone age assessment to measure the skeletal maturity of children and to predict the future height. These discrepancies are good indicators for diagnosing growth disorders. Normally, left hand skeletal is employed in this assessment. The low quality of ossification sites of carpals deteriorates the pediatrician’s visibility in inspecting the pertinent radiographic manifestations. This in turn affects the bone age assessment. Therefore, we have to enhance the quality before assessing them. Histogram equalization is one of the contrast enhancement techniques that suit this type of enhancement. Existing histogram equalizations, however, are confronting with problems in preserving the brightness …

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Helion’S Snapshot Module, Nii-Kwartei Quartey Jul 2020

Helion’S Snapshot Module, Nii-Kwartei Quartey

Cybersecurity Undergraduate Research Showcase

During my undergraduate research, I spent my time working with a home automation program known as Helion, specifically, its Snapshot module. I was tasked with learning new material and completing part of the webpage that were unfinished. I also had to get a little creative when working on a design that users could find appealing. There were times I found working on Helion difficult but overall, working with Helion’s Snapshot Module is something that will help me improve with my undergraduate studies.

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A Review On Eye-Tracking Metrics For Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah Jul 2020

A Review On Eye-Tracking Metrics For Sleepiness, Debasis Roy, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Sleepiness that can arise from sleep deprivation can increase human errors in task performance and create workplace hazards and accidents. Hence, it is critical to detect sleepiness to minimize hazards and human errors. This paper provides a review of the literature on eye tracking metrics that can be used to detect sleepiness. These metrics include blink duration, blink frequency, saccade latency, saccade peak velocity, saccade accuracy, smooth pursuit velocity gain, fixation rate, pupil size, and latency to pupil constriction.

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Improving Event Detection Via Open-Domain Event Trigger Knowledge, Meihan Tong, Bin Xu, Shuai Wang, Yixin Cao, Lei Hou, Juanzi Li, Jun Xie Jul 2020

Improving Event Detection Via Open-Domain Event Trigger Knowledge, Meihan Tong, Bin Xu, Shuai Wang, Yixin Cao, Lei Hou, Juanzi Li, Jun Xie

Research Collection School Of Computing and Information Systems

Event Detection (ED) is a fundamental task in automatically structuring texts. Due to the small scale of training data, previous methods perform poorly on unseen/sparsely labeled trigger words and are prone to overfitting densely labeled trigger words. To address the issue, we propose a novel Enrichment Knowledge Distillation (EKD) model to leverage external open-domain trigger knowledge to reduce the in-built biases to frequent trigger words in annotations. Experiments on benchmark ACE2005 show that our model outperforms nine strong baselines, is especially effective for unseen/sparsely labeled trigger words. The source code is released on https://github.com/shuaiwa16/ekd.git.

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A Process Model For Designing Performance Dashboard Using Visualization Techniques, Bahar Muhammad Nasim Jul 2020

A Process Model For Designing Performance Dashboard Using Visualization Techniques, Bahar Muhammad Nasim

Student Works (2020-2029)

Data visualization is the presentation of data in a pictorial or graphical format. It enables decision-makers to see data analysis presented visually, so they can observe difficult concepts or identify new patterns. With interactive visualization, we can take the concept a step further by using technology to drill down into charts and graphs for more detail, interactively changing what data see and how it is processed. With the help of data visualization, it is expected to promote creative data exploration. A performance dashboard is one of the most common use cases for data visualization, and it enables decision-makers such as …

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Unsupervised Monocular Depth Estimation With Multi-Scale Structural Similarity Powered Loss Function, Kohan Ali Jul 2020

Unsupervised Monocular Depth Estimation With Multi-Scale Structural Similarity Powered Loss Function, Kohan Ali

Student Works (2020-2029)

Depth Estimation refers to a set of techniques and algorithms that aim to obtain a representation of spatial information of a scene. Nowadays specific hardware such as sensors, radars and multiple-view-recording cameras are being used in order to acquire depth data of a scene. Modern approaches use deep learning to address this task by trying to learn depth information in a supervised manner. However, this approach requires a large amount ground-truth data for a particular scene so that a model can be trained successfully. Also preparing ground-truth data for a range of environments is a challenging and expensive task to …

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Hyperbolic Visual Embedding Learning For Zero-Shot Recognition, Shaoteng Liu, Jingjing Chen, Liangming Pan, Chong-Wah Ngo, Tat-Seng Chua, Yu-Gang Jiang Jun 2020

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 …

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Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun Jun 2020

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 …

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Visual Commonsense Representation Learning Via Causal Inference, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun Jun 2020

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 …

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Self-Trained Deep Ordinal Regression For End-To-End Video Anomaly Detection, Guansong Pang, Cheng Yan, Chunhua Shen, Anton Van Den Hengel, Xiao Bai Jun 2020

Self-Trained Deep Ordinal Regression For End-To-End Video Anomaly Detection, Guansong Pang, Cheng Yan, Chunhua Shen, Anton Van Den Hengel, Xiao Bai

Research Collection School Of Computing and Information Systems

Depression is among the most prevalent mental disorders, affecting millions of people of all ages globally. Machine learning techniques have shown effective in enabling automated detection and prediction of depression for early intervention and treatment. However, they are challenged by the relative scarcity of instances of depression in the data. In this work we introduce a novel deep multi-task recurrent neural network to tackle this challenge, in which depression classification is jointly optimized with two auxiliary tasks, namely one-class metric learning and anomaly ranking. The auxiliary tasks introduce an inductive bias that improves the classification model’s generalizability on small depression …

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