Theseus - Selaus asiasanan mukaan "deep learning"
Viitteet 21-40 / 100
-
Comparing Path-Finding Algorithms and Machine Learning Model
(2024)This thesis focused on comparing A-star algorithm and some of its variants against Q-learning and Proximal Policy Optimization algorithms in terms of path finding and in game development perspective. Both Q-learning and ... -
Computational mathematics behind generative AI and machine learning
(2024)Neural networks have revolutionized various fields of computer science, especially machine learning and artificial intelligence. The purpose of this thesis was to examine the fundamentals of neural networks, overview the ... -
Cyberattacks on critical infrastructure and corresponding countermeasures
(2023)These days cyberattacks pose a growing risk to cyber-physical systems (CPSs) that act as a part of critical infrastructure (CI) that are vital to a nation’s economy and security. These attacks can disrupt vital devices and ... -
Data-Driven Innovation: The Potential of Synthetic Data through Generative AI
(2024)Data scarcity constitutes a protracted challenge to AI decision-making across data-driven industries. Research has shown that demand for larger training datasets is growing, but the current method for data collection has ... -
Deciphering Ancient Chinese Scripts with Convolutional Neural Networks : A Study on Calligraphic Styles in Classical Chinese Texts
(2023)The primary objective of this study was to employ deep learning algorithms, specifically convolutional neural networks (CNN), to identify and classify calligraph styles in classical Chinese texts. Samples representing four ...Rajattu käyttöoikeus / Restricted access / Tillgången är begränsad -
Deep learning
(2022)This thesis builds upon work carried out by the author of this thesis recently on deep learning to build a computer vision deep learning pipeline using Generative Adversarial Networks (GANs). For much of the work, agile ...Rajattu käyttöoikeus / Restricted access / Tillgången är begränsad -
Deep Learning EEG-based Motor Imagery System for Robot Control using 3D Printed Headset and Electrodes
(2023)This thesis describes the design and implementation of an EEG-based motor imagery system for robot control using a 3D printed headset and electrodes. The primary aim was to create a more comfortable and user-friendly EEG ... -
Deep Learning for Toxic Comment Detection in Online Platforms
(2023)This research aimed to explore the use of Deep Learning Artificial Neural Networks (ANNs) for toxic comment classification on social media and online forums. The prevalence of toxic interactions on these platforms has ... -
Deep Learning-based Table Detection in Documents
(2023)Extracting content from tables in documents was identified as problematic, especially in the cases of tables without clear borders. The proposed solution was to apply document layout analysis, particularly using the ... -
Deep Reinforcement Learning Implementation for Vessel Stability Calculations
(2024)This paper focused on combining ships stability calculations with deep reinforcement learning methods. For the sake of this thesis the author developed a proof of concept software that not only enables users to solve tasks ... -
Detection of Anomalies in Electric Vehicle Charging Sessions Data
(2024)Anomalies, or outliers, in data are deviations from expected patterns and can result from errors, rare events, system glitches, or fraudulent activities. Understanding anomalies is crucial across industries, as they can ... -
Developing a Video Summarizing Tool using Machine Learning
(2022)In recent years, video has become a highly significant form of visual data, and the explosion of short video platforms like TikTok, Instagram, and Facebook has led people to prefer to consume short content than watching a ... -
Developing an efficient attack detection model for an industrial control system using CNN-based approaches : attack detection using PS-CNN
(2023)Industrial Control Systems (ICS) critical infrastructures, including thermal plants, water treatment plants, nuclear plants, oil refineries, and gas pipelines, rely on uninterrupted operations. With the transformation of ... -
Developing LLM-powered Applications Using Modern Frameworks
(2024)Tekoälyn (AI) kehitys on viime vuosina ollut erittäin nopeaa. Teoreettisen tutkimuksen edistysaskeleet, sekä merkittävä kasvu laskentatehossa ovat mahdollistaneet yhä kehittyneempien ja monimutkaisempien tekoälymallien ... -
Diagnosis of Breast Cancer using Deep learning
(2019)This project covers the fundamentals knowledge of artificial intelligence in general and deep learning in particular, covers the vision of technologies developed in the future. Artificial intelligent becomes more necessary ... -
Dog/cat image recognition with React, Flask, and TensorFlow
(2022)Data plays an essential role in modern life. The real world produces billions of bytes of data per day, and the 90 percentage of data in 2019 is double the amount of data last two years (Statista Research Department. 2022). ...Rajattu käyttöoikeus / Restricted access / Tillgången är begränsad -
Enhancing Anti-Money Laundering Strategies Using Artificial Intelligence
(2024)Vaikka tekoälyä on käytetty eri aloilla jo vuosia, rahanpesun torjunta on suurelta osin tukeutunut perinteisiin, sääntöihin perustuviin menetelmiin. Opinnäytetyö tutkii, kuinka rahanpesun torjunnan strategioita voidaan ...Rajoitettu käyttöoikeus / Restricted access / Tillgången begränsad -
Enhancing Customer feedback processing with Machine Learning in Microsoft Azure
(2022)Text Classification and Natural Language Processing (NLP) is developing fast, and all the applications are rapidly evolving, GPT-3 emerged in the field just last year and there are some open-source options in the field, ... -
Enhancing Security : Deep Learning Models for Anomaly Detection in Surveillance Videos
(2024)An extensive study on effective methods to detect anomalous events in surveillance videos is presented in this research. An increasing demand for reliable and efficient anomaly detection systems capable of identifying ... -
Enhancing Tetris Gameplay with Deep Reinforcement Learning
(2024)This work's principal purpose was to create an artificial intelligence solution for the well-known Tetris game, which was totally constructed in C++ since there aren't many online resources in this subject. Furthermore, ...















