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Full-Text Articles in Physical Sciences and Mathematics

Uc-43 Aletheianomous Ai: The Chat Bot Providing The Most Accurate Knowledge Information, David E Chavarro, Aimi Tran, Ethan B Byrd, Matthew J Fincher Apr 2024

Uc-43 Aletheianomous Ai: The Chat Bot Providing The Most Accurate Knowledge Information, David E Chavarro, Aimi Tran, Ethan B Byrd, Matthew J Fincher

C-Day Computing Showcase

For this project, our group aimed to create an intelligent chat bot that was accessible through the web client interface. Aletheianomous, our chat bot, was designed to provide accurate information ethically, aligned with human values. When applicable, the AI would offer the user citations to support its responses. For the back-end, a virtual machine (VM) server in AWS with access to the Graphics Processing Unit (GPU) would run three types of models: Sentence Separation Model, Search Query Extractor Model, and the Response Model. The front-end server using Microsoft Azure generates the web page for the user, exchanges chat data with …

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Uc-48 Birding With Buddy, Lazare V Sawadogo, Ikhelowa E Adeji, Blake Graham, Zach Alpine, Troy C Sorrells Apr 2024

Uc-48 Birding With Buddy, Lazare V Sawadogo, Ikhelowa E Adeji, Blake Graham, Zach Alpine, Troy C Sorrells

C-Day Computing Showcase

Birding with Buddy is an educational and entertaining immersive virtual 3D low-poly birdwatching to be experienced at the Carter Lake Nature Center to enable kids to embark on a quest to learn more about birds. Buddy the Beaver guides the user through different terrain types to identify diverse bird species with sounds. Integrate a bird identification system where players click on the binocular icon to switch to a binocular view. In this view, players can choose to Identify (multiple-choice) the correct bird, Hear the Call Again, or Consult a Field Guide. Featuring flippable pages with images and notable markings of …

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Ur-89 Performance Analysis Of Post-Quantum Computing Key Encapsulation Mechanism Algorithms, Dillon J Horton, Jose Gutierrez, Tyler G Standard Apr 2024

Ur-89 Performance Analysis Of Post-Quantum Computing Key Encapsulation Mechanism Algorithms, Dillon J Horton, Jose Gutierrez, Tyler G Standard

C-Day Computing Showcase

Within the next twenty years or so experts predict that we will have quantum computers which will make certain kinds of encryption that we rely on ineffective and vulnerable to malicious entities. Post quantum computing (PQC) algorithms fill in that security gap that classical encryption algorithms can not. A particular category of PQC algorithms are key exchange mechanism (KEM) algorithm. The goal of these algorithms is to securely generate a shared symmetric key which can be used for encrypting future communication between the hosts. An important use case for these algorithms is in securing the Transport Layer Security protocol (TLS) …

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Uc-60 Myfoodscan, Ibrahima Gueye, Brianna J Noel, Victoria O Kuswita, Je'dae Lisbon Apr 2024

Uc-60 Myfoodscan, Ibrahima Gueye, Brianna J Noel, Victoria O Kuswita, Je'dae Lisbon

C-Day Computing Showcase

MyFoodScan is a mobile app that enables users to scan barcodes of various food and drink items to ensure they are in compliance with their specific dietary needs. Individuals utilize this application to make a customized profile based on diet, such as vegan, vegetarian, dairy-free, allergies, etc. MyFoodScan promotes compliance with dietary limitations. The application was developed with React Native, Expo Go, Google Firebase, using the React Native Camera for barcode scanning. The OpenFoodFacts API database is used for product information. The goal of this application is to enhance awareness and safety for various dietary needs and monitor dietary restrictions.

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Ur-62 Deep Learning Approach To Network Anomaly Detection, Rene P Lisasi, Jamia M Jackson Apr 2024

Ur-62 Deep Learning Approach To Network Anomaly Detection, Rene P Lisasi, Jamia M Jackson

C-Day Computing Showcase

A model of network anomaly detection capable of detecting a multitude of network attacks. This model is based on the hypothesis that by studying a system’s network records for irregular patterns during system usage, network anomalies can be identified. This model contains information about the type of attacks and metrics. This model is to be used in any type of distributed environment. The general purpose of this model is to detect when an attack is or has happened using deep learning techniques to optimize the training speed, accuracy and robustness of attack detection. This is done to stop the epidemic …

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Uc-75 Mineticket Discord Ticket Management Bot, Dean Rice, Arturo Martinez, Grace Shell, Solomon Thao, Palmer Brown Apr 2024

Uc-75 Mineticket Discord Ticket Management Bot, Dean Rice, Arturo Martinez, Grace Shell, Solomon Thao, Palmer Brown

C-Day Computing Showcase

We made use of the discord.py python library to manage the framework of the bot, since discord relies on a RESTful API for all of its bots. This layer of abstraction allowed us to focus on the important things, such as sanitizing inputs for SQL queries and building out a large, fully customizable feature set so future adjustments are made simple and easy as changing entries within a configuration file. Our goal was to make the bot as easy to update as possible, with the hope that, should requirements change in the future, the sponsor can quickly modify existing code …

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Uc-81 Drinkinator App, Maximus A Smith, Toby Mose, Grayson Payne Apr 2024

Uc-81 Drinkinator App, Maximus A Smith, Toby Mose, Grayson Payne

C-Day Computing Showcase

The "Drinkinator" app represents an innovative solution aimed at revolutionizing the beverage industry by providing users with a personalized drink recommendation system. Rooted in a motivation to diversify people's beverage selections and enhance their drinking experiences, the app facilitates exploration of a wide range of mixed drinks, wines, and beers tailored to individual preferences. Leveraging data analysis and user profiling techniques, the app offers tailored suggestions, showcasing a deep understanding of consumer behavior and taste preferences. Utilizing React Native for front-end development and JavaScript for back-end functionality, the app integrates various libraries to ensure seamless user experiences and efficient data …

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Uc-71 An Environmentally Conscious Roguelike, Andrew Bland, Brendan Strawser, Adele Rousseau, Bewaji Adewunmi Apr 2024

Uc-71 An Environmentally Conscious Roguelike, Andrew Bland, Brendan Strawser, Adele Rousseau, Bewaji Adewunmi

C-Day Computing Showcase

This semester we have been creating an action-adventure video game based on the theme of "Saving the Environment".

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Uc-73 Spacewalkers: Tilt 5, Charles D Mossor, Jacob Hundley, Ifran Ambahun, Joshua Whorton Apr 2024

Uc-73 Spacewalkers: Tilt 5, Charles D Mossor, Jacob Hundley, Ifran Ambahun, Joshua Whorton

C-Day Computing Showcase

Our project (and presentation as a whole) is to create an immersive and fun casual game experience using the Tilt 5 system. We made a tower defense game that uses the player’s input with the Tilt 5 in order to defend against enemies. By delivering a variety of enemies, levels, and towers in our game, we further enhanced the experience.

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Uc-51 Difference Detection: Automated Defect Detection System For Modernized Display Units, Umer Aziz, Harrison Rosser, Urooj Arshad, Teonta N Pegues, Katherine Vu Apr 2024

Uc-51 Difference Detection: Automated Defect Detection System For Modernized Display Units, Umer Aziz, Harrison Rosser, Urooj Arshad, Teonta N Pegues, Katherine Vu

C-Day Computing Showcase

In today's high-stakes military environments, the reliability and accuracy of software systems are paramount. Defects within these systems not only pose significant financial risks but can also endanger lives. To ensure the utmost safety and effectiveness, military systems undergo extensive testing and validation processes. However, the lifespan of these systems is far from indefinite. Environmental changes, advancements in adversarial capabilities, evolving mission requirements, and parts obsolescence necessitate continuous improvement efforts. One critical area of focus is the modernization of display units, which are vital for providing pilots with essential mission information and ensuring their safe return. The 402 Software Engineering …

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Uc-56 Donation For Dummies, Jayvon L Triplett, Stephen A Mancini, Mitchell Thomason, Kendrell M Niles Apr 2024

Uc-56 Donation For Dummies, Jayvon L Triplett, Stephen A Mancini, Mitchell Thomason, Kendrell M Niles

C-Day Computing Showcase

Donation For Dummies is a VR game designed to help people feel more relaxed and informed when donating blood. It consists of a theater room where a video plays explaining the process as well as what to do before and after donating. For people wanting a distraction, we have an arcade where players can enjoy minesweeper, matching, or solitaire. For those wishing to relax, we have an art gallery where players can virtually walk around and look at various pieces of art. The more relaxed player that do not wish to move around the game world can instead choose to …

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Uc-92 Faculty Course Analysis Report Self Service Interface, Meet Patel, Trevor Harbin, Omit Deb, Edwin Mayhew Apr 2024

Uc-92 Faculty Course Analysis Report Self Service Interface, Meet Patel, Trevor Harbin, Omit Deb, Edwin Mayhew

C-Day Computing Showcase

This project aims to enhance the efficiency of generating and submitting Faculty Course Analysis Reports (FCARs) for the faculty of CCSE in accordance with ABET accreditation requirements. The scope involves the design and implementation of a locally hosted web-based application. This application will streamline the process, allowing FCARs to be requested and generated in real time. Development will be conducted on a Linux-based platform, and security measures will be integrated based on the NetID system.

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Uc-85 Helpr: Helping Extrapolate Labels For Police Reports Using Large Language Models, Hailey N Walker, William A Stigall Apr 2024

Uc-85 Helpr: Helping Extrapolate Labels For Police Reports Using Large Language Models, Hailey N Walker, William A Stigall

C-Day Computing Showcase

Police officers spend many hours a week documenting their findings when reporting to a 911 call. There is so much detail in these reports that they remain an untapped resource for future data analytics by the police department. The reports are currently being analyzed by human experts and categorized into the following categories: “Substance Abuse”, “Mental Health”, “Domestic/Social”, “Nondomestic/Social”, and “Other”. To assist the experts and reduce the amount of time that is spent on reading and analyzing, we are proposing the use of large language models (LLMs) to tag police reports based on their content. Two models, Mistral-7B and …

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Uc-20 Playlist Synch, Joshua Poore, Nikita D Smith, Ben S Pallotti Apr 2024

Uc-20 Playlist Synch, Joshua Poore, Nikita D Smith, Ben S Pallotti

C-Day Computing Showcase

Our project is a web application that allows users to sign in and transfer music playlists from one music streaming service to another. Currently, it is only functional with Apple and Spotify music but there are plans to implement more in the future.

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Uc-24 Wildling Rumble, Logan Haines, Ryan A Whisenhunt Apr 2024

Uc-24 Wildling Rumble, Logan Haines, Ryan A Whisenhunt

C-Day Computing Showcase

When it comes to the combined field of digital board games, there needs to be a balance of what is necessary for the physical space and what is necessary for the digital space. The game must be justified as a combination of the two elements and not be able to shift completely to either side. In this study, we are exploring a new modality that uses Near Field Communication cards for transferring game data to the application. Our new method eases the requirement on players to keep track of the game state, as that is handled separately from the program.

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Uc-120 Virtual Companionship Chatbot, Cesar Tortolero, Rakshak Gurung, Noah Clark, Fabritzzio A Cabrejos Apr 2024

Uc-120 Virtual Companionship Chatbot, Cesar Tortolero, Rakshak Gurung, Noah Clark, Fabritzzio A Cabrejos

C-Day Computing Showcase

Loneliness affects about 77% of college students at some point, highlighted by a Gitnuss report. Our project aims to mitigate this by introducing a personalized chatbot that serves as an emotional outlet for students. The application is built on a React Native frontend, employs a DistilGPT-2 language model using the QUAC dataset, and is backed by a Python server. We plan to deploy it on an Azure NC6s_v3 Cloud server, integrating Firebase Real-Time Database for Android and iOS compatibility.

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Gmr-107 An Integrated Architecture For Maintaining Security In Cloud Computing Using Blockchain, Namratha Tavva, Ashrith Kumar Devara, Gar H Lock Apr 2024

Gmr-107 An Integrated Architecture For Maintaining Security In Cloud Computing Using Blockchain, Namratha Tavva, Ashrith Kumar Devara, Gar H Lock

C-Day Computing Showcase

Cloud services are vulnerable to assaults because of their widespread availability. Since cloud computing is still a relatively new service, there is a real risk that sensitive information might be altered while in transit. Because of this, bad actors may gain an edge by manipulating data. Clients using the cloud for a wide range of use cases want to know that their data is reliable and secure. Blockchain, on the other hand, is an immutable digital ledger that may be used with cloud computing to provide an immutable cloudbased data storage and processing system. In this work, we present a …

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Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati Apr 2024

Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati

C-Day Computing Showcase

With the quick rise of Artificial Intelligence (AI), generative AI models have greatly increased the volume and velocity of data creation. Among that data, AI-generated images have become a highly discussed topic, especially when discussing the potential dangers of these AI models. Due to these dangers, being able to distinguish AI-generated art from human-made art is becoming a necessity. Additionally, as these AI-models improve, it is becoming increasingly difficult for humans to determine whether art is AI-generated or human-made. This paper proposes the further exploration of the effectiveness of a current state of the art AI-image identification model.

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Uc-64 Smart Evaluator Of Indirect Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes Apr 2024

Uc-64 Smart Evaluator Of Indirect Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes

C-Day Computing Showcase

The Smart Evaluator is a web-based software solution that analyzes industrial tools and their vending possibilities. It aims to streamline inventory research for sales teams, reducing manual data gathering and vendibility determination. To begin, users simply upload a basic item inventory spreadsheet, and start the program. From there, the program uses web scraping and ChatGPT to gather key data about the various tools including dimensions, weight, and fragility. Each item is then evaluated based on the collected data, and the optimum storage method is calculated. Once these tasks are performed, the results are stored in the system’s database for future …

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Ur-116 Enhancing Engineering Education Through Llm-Driven Adaptive Quiz Generation, Devananda Sreekanth, Sreekanth Gopi Apr 2024

Ur-116 Enhancing Engineering Education Through Llm-Driven Adaptive Quiz Generation, Devananda Sreekanth, Sreekanth Gopi

C-Day Computing Showcase

This study aims to develop an Artificial Intelligence (AI) quiz generation system for engineering students to enhance personalized learning. In the rapidly evolving field of educational education, the emergence of AI and, more specifically, Large Language Models (LLMs) such as GPT-4, Llama, Claude, and Gemini, has marked a significant advancement. Our literature review method employs a systematic approach, analyzing peer-reviewed articles, conference papers, and authoritative reports to uncover the trends and challenges in AI-driven quiz generation. The notable gap identified in our literature review is the lack of LLM-based quiz generation methods specifically for engineering education, which incorporate interactive and …

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Ur-49 Coronary Artery Segmentation Using Convolutional Neural Network, Connor Bell, Brenda Nyiam, Daron L Pracharn Apr 2024

Ur-49 Coronary Artery Segmentation Using Convolutional Neural Network, Connor Bell, Brenda Nyiam, Daron L Pracharn

C-Day Computing Showcase

The project contributes to the advancement of medical imaging technology by overcoming the challenges associated with segmenting coronary arteries from ICA images. By leveraging deep learning algorithms, the system can effectively extract coronary arteries with high accuracy, providing valuable information for CAD diagnosis and treatment planning. Accurate and efficient coronary artery segmentation can improve the workflow of cardiologists and enhance the quality of patient care. A robust automated segmentation model could potentially reduce the time and resources required for manual annotation by experienced cardiologists, leading to cost savings and increased efficiency in clinical settings. Additionally, the developed model could be …

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Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson Apr 2024

Ur-70 Faster Inequivalence Testing Using Robustness, Emily G Jackson

C-Day Computing Showcase

We propose a new method for quickly testing the inequivalence of two Boolean functions, when one function is represented as an ordered binary decision diagram (OBDD), and the other is represented in conjunctive normal form (CNF). Our approach is based on a notion of classifier robustness from the fields of explainable AI (XAI) and adversarial machine learning. In particular, we show that two Boolean functions that are very similar in terms of their truth values, can be very different in terms of their robustness, which in turn, provides a witness to their inequivalence. A more efficient approach to inequivalence testing …

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Gc-67 Automatic Daily Financing Headlines Collection, Storage, Analysis And Presentation, Sahithi Atimamula, Jasminn O Evans, Julian Reyes, Victoria Castro, Krista G Settle Apr 2024

Gc-67 Automatic Daily Financing Headlines Collection, Storage, Analysis And Presentation, Sahithi Atimamula, Jasminn O Evans, Julian Reyes, Victoria Castro, Krista G Settle

C-Day Computing Showcase

The "Automatic Daily Financing Headlines Collection, Storage, Analysis, and Presentation" project aims to streamline the process of gathering financial headlines from financial news sources, storing them systematically, performing analysis, and presenting the insights in a user-friendly format. This automation project is designed to provide timely and relevant financial information to users interested in staying informed about market trends, economic news, and financial events. By automating the entire workflow, users can stay informed, make data-driven decisions, and navigate the dynamic landscape of financial news with ease. The project embodies the fusion of automation, data analytics, and user-centric design to create a …

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Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota Apr 2024

Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota

C-Day Computing Showcase

Predicting house prices is a challenging task that researchers from various fields (economics, statistics, politics, etc.) have attempted to answer. An accurate house prediction is useful not only to policymakers to improve their policies, but also to help sellers and buyers in the real estate market make well- informed decisions. Commonly, prediction models are trained on the whole dataset. However, as Azimlu et al [1] suggested, such models might not perform very well on dispersed data. They propose a new approach which first divides the whole dataset into smaller clusters, and then each cluster would be trained with an appropriate …

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Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam Apr 2024

Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam

C-Day Computing Showcase

In the rapidly evolving fields of Artificial Intelligence and Natural Language Processing, significant opportunities have emerged to transform educational practices. Discourse analysis, particularly in science education, plays a critical role in fostering scientific thinking among students. However, the manual application of tools like the Classroom Discourse Analysis Tool is resource-intensive and impractical on a large scale. This abstract proposes the development of an AI-based Discourse Analysis System tailored for educational settings, designed to automate and enrich the analysis of classroom discourse. Leveraging the latest in Artificial Intelligence and Natural Language Processing, this web-based application will provide teachers nationwide with the …

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Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher Apr 2024

Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher

C-Day Computing Showcase

Advancements in the field of machine learning have led to object detection systems that can approach or even improve upon human performance. Based on deep learning, these systems play a crucial role in many aspects, and continue to be improved on and see expanded adoption. However, these systems are vulnerable to adversarial attacks that rely on targeted noise to spoof detection. Researchers have applied this concept to increase real world adversarial performance by restricting this noise to a patch that can be placed on new images to disrupt object detection. Previous research has focused on patches applied to person recognition …

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Evaluating Introductory Computer Science Labs In The Presence Of Ai Tools, Nicholas Snow, Devin Chaimberlain, Abigail Pitcairn, Benjamin Sweeney Apr 2024

Evaluating Introductory Computer Science Labs In The Presence Of Ai Tools, Nicholas Snow, Devin Chaimberlain, Abigail Pitcairn, Benjamin Sweeney

Thinking Matters Symposium

This study explores the resistance of introductory computer science lab assignments to “shortcutting” by generative AI tools, such as ChatGPT. By analyzing the work of three distinct student personas on these assignments, we identified key characteristics of language and structure that influence an assignment's vulnerability to AI abuse. Based on these insights, we propose strategies for educators to adapt labs to both counteract AI shortcutting and encourage productive uses of AI.

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A System Of Communication Between Two Computers Using Novel Frequency Shift Keying Techniques, Jared Reyes Apr 2024

A System Of Communication Between Two Computers Using Novel Frequency Shift Keying Techniques, Jared Reyes

Honors Thesis

Frequency shift keying (FSK) is an old but powerful form of modulation that powered much of the early modems of the 1960’s, and the author felt inspired to make his own version of audio binary FSK modulation. He researched the general history and legacy of the Bell 103, a modem using FSK that defined telecommunication for the next few decades. Using research of the most common English characters of recent emails to determine which English characters should have the shortest bit length, a novel character encoding standard was created using variable bit rate. In addition, he has created a modulation …

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Artificial Intelligence And Film: A Journey In Public Perception From 1960 To The Present Day, Kayla Anderson, Andrew Roggeman, Joseph Fuller Apr 2024

Artificial Intelligence And Film: A Journey In Public Perception From 1960 To The Present Day, Kayla Anderson, Andrew Roggeman, Joseph Fuller

Celebrating Scholarship and Creativity Day (2018-)

An analysis of accomplishments in film from the 1960s-2020s that feature Artificial Intelligence to give a full picture of how public perception has changed towards these technologies over time, supplemented by historical and technological context.

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Semantic Segmentation Of Point Cloud Sequences Using Point Transformer V3, Marion Sisk Apr 2024

Semantic Segmentation Of Point Cloud Sequences Using Point Transformer V3, Marion Sisk

Master's Theses

Semantic segmentation of point clouds is a basic step for many autonomous systems including automobiles. In autonomous driving systems, LiDAR sensors are frequently used to produce point cloud sequences that allow the system to perceive the environment and navigate safely. Modern machine learning techniques for segmentation have predominately focused on single-scan segmentation, however sequence segmentation has often proven to perform better on common segmentation metrics. Using the popular Semantic KITTI dataset, we show that by providing point cloud sequences to a segmentation pipeline based on Point Transformer v3, we increase the segmentation performance between seven and fifteen percent when compared …

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