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Graphics and Human Computer Interfaces Commons™
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Articles 1 - 6 of 6
Full-Text Articles in Graphics and Human Computer Interfaces
Daot: Domain-Agnostically Aligned Optimal Transport For Domain-Adaptive Crowd Counting, Huilin Zhu, Jingling Yuan, Xian Zhong, Zhengwei Yang, Zheng Wang, Shengfeng He
Daot: Domain-Agnostically Aligned Optimal Transport For Domain-Adaptive Crowd Counting, Huilin Zhu, Jingling Yuan, Xian Zhong, Zhengwei Yang, Zheng Wang, Shengfeng He
Research Collection School Of Computing and Information Systems
Domain adaptation is commonly employed in crowd counting to bridge the domain gaps between different datasets. However, existing domain adaptation methods tend to focus on inter-dataset differences while overlooking the intra-differences within the same dataset, leading to additional learning ambiguities. These domain-agnostic factors,e.g., density, surveillance perspective, and scale, can cause significant in-domain variations, and the misalignment of these factors across domains can lead to a drop in performance in cross-domain crowd counting. To address this issue, we propose a Domain-agnostically Aligned Optimal Transport (DAOT) strategy that aligns domain-agnostic factors between domains. The DAOT consists of three steps. First, individual-level differences …
Equivariance And Invariance Inductive Bias For Learning From Insufficient Data, Tan Wang, Qianru Sun, Sugiri Pranata, Karlekar Jayashree, Hanwang Zhang
Equivariance And Invariance Inductive Bias For Learning From Insufficient Data, Tan Wang, Qianru Sun, Sugiri Pranata, Karlekar Jayashree, Hanwang Zhang
Research Collection School Of Computing and Information Systems
We are interested in learning robust models from insufficient data, without the need for any externally pre-trained model checkpoints. First, compared to sufficient data, we show why insufficient data renders the model more easily biased to the limited training environments that are usually different from testing. For example, if all the training "swan" samples are "white", the model may wrongly use the "white" environment to represent the intrinsic class "swan". Then, we justify that equivariance inductive bias can retain the class feature while invariance inductive bias can remove the environmental feature, leaving only the class feature that generalizes to any …
A Bidirectional Formulation For Walk On Spheres, Yang Qi
A Bidirectional Formulation For Walk On Spheres, Yang Qi
Dartmouth College Master’s Theses
Poisson’s equations and Laplace’s equations are important linear partial differential equations (PDEs)
widely used in many applications. Conventional methods for solving PDEs numerically often need to
discretize the space first, making them less efficient for complex shapes. The random walk on spheres
method (WoS) is a grid-free Monte-Carlo method for solving PDEs that does not need to discrete the
space. We draw analogies between WoS and classical rendering algorithms, and find that the WoS
algorithm is conceptually identical to forward path tracing.
We show that solving the Poisson’s equation is equivalent to solving the Green’s function for every
pair of …
Gauging The State-Of-The-Art For Foresight Weight Pruning On Neural Networks, Noah James
Gauging The State-Of-The-Art For Foresight Weight Pruning On Neural Networks, Noah James
Computer Science and Computer Engineering Undergraduate Honors Theses
The state-of-the-art for pruning neural networks is ambiguous due to poor experimental practices in the field. Newly developed approaches rarely compare to each other, and when they do, their comparisons are lackluster or contain errors. In the interest of stabilizing the field of pruning, this paper initiates a dive into reproducing prominent pruning algorithms across several architectures and datasets. As a first step towards this goal, this paper shows results for foresight weight pruning across 6 baseline pruning strategies, 5 modern pruning strategies, random pruning, and one legacy method (Optimal Brain Damage). All strategies are evaluated on 3 different architectures …
An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson
An Investigation Into, And The Construction Of, An Operable Windows Notifier, Grey Hixson
Computer Science and Computer Engineering Undergraduate Honors Theses
The Office of Sustainability at the University of Arkansas identified that building occupants that have control over operable windows may open them at inappropriate times. Windows opened in a building with a temperature and air differential leads to increased HVAC operating costs and building occupant discomfort. This led the Associate Vice Chancellor of Facilities at the University of Arkansas to propose the construction of a mobile application that a building occupant can use to make an informed decision before opening their window. I have formulated a series of research objectives in conjunction with the Director of the Office of Sustainability …
Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan
Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan
Computer Science and Computer Engineering Undergraduate Honors Theses
The combination of Bluetooth Low energy and E-Ink displays allow for a low energy wire-less display. The application of this technology is far reaching especially given how the Bluetooth Low Energy specification can be extended. This paper proposes an extension to this specification specifically for inventory tracking. This extension combined with the low energy E-Ink display results in a smart label that can keep track of additional meta data and inventory counts for physical inventory. This label helps track the physical inventory and can help mitigate any errors in the logical organization of inventory.