Theseus - Selaus asiasanan mukaan "deep learning"
Viitteet 61-80 / 100
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Layout Aware Textmaps: an approach to preserve two-dimensional textual structure of expense documents on machine learning based information extraction
(2023)Automatic information extraction from scanned receipts and invoices is a task that is both widely researched and adopted in various businesses. With an ever-increasing demand on improving performance of business processes, ... -
Learning by Playing: A Stock Market Simulation Game With Deep Reinforcement Learning-powered NPCs
(2024)The research explored Deep Reinforcement Learning (DRL) to enhance educational simulation games for business education, focusing on the stock market. The key challenge was integrating real-world data into an engaging ... -
Machine Learning aided Linux Kernel Code Analysis
(2024)Jokainen koodimuutos, jota ehdotetaan Linux-käyttöjärjestelmäytimeen, testataan monilla eri automaattisilla testeillä. Tästä huolimatta jokainen muutos on vaatinut ihmisten tekemän katselmoinnin. Johtuen rajallisesta ... -
Machine Vision for Sorting
(2024)The integration of robots and machine vision in manufacturing has significantly advanced automation, reducing labour costs and improving productivity and safety. This thesis investigates the effectiveness of three object ... -
Mobile machine anomaly detection in container handling operations
(2023)The objective of this Master’s thesis is to research Deep Learning (DL) based anomaly detection methods for unlabeled time series data in container handling operations. Detected anomalies can be the sign of a defect in the ... -
Model fooling attacks against medical imaging: a short survey
(ProCon, 2020)This study aims to find a list of methods to fool artificial neural networks used in medical imaging. We collected a short list of publications related to machine learning model fooling to see if these methods have been ... -
Neural Network Eye Tracking:Determining Nine-Grid Regions & Application
(2023)As technology advances, the development of mobile platforms has nearly reached saturation. AR/MR (Augmented or Mixed Reality) eyewear is anticipated to be the new type of product leading technological advancements in the ... -
Neural Networks and Their Internal Processes: From the ground up
(2022)The theses’ aim is to explain and practically show the operation of different types of neural networks. Thesis will prove that they all have the same main idea at the core but have different goals, methods and components. ... -
Neural Networks and Their Internal Processes: From the ground up
(2022)The aim of this thesis is to explain and practically show the operation of different types of neural networks. The thesis will prove that they all have the same primary idea at the core but have different goals, methods, ... -
Next generation of NPC dialogue: creating responsive NPCs (Non-Player Characters) with Retrieval-Augmented Generation and real-time player data
(2024)Suurten kielimallien (LLM), Retrieval-Augmented Generation (RAG) -tekniikan ja reaaliaikaisten pelaajatapahtumien integrointia ei-pelaajahahmojen (NPC) kehittämisessä videopeleissä tutkittiin parantaakseen dialogien ... -
Open-source dog breed identification using CNN: explanation of the development & underlying technological specifications
(2023)This thesis aims to develop a deep learning model that uses the Fast.ai library and transfer learning to create a convolutional neural network model. The model will identify dog breeds in digital images and evaluate the ... -
Optimizing energy consumption and production with energy management system
(2024)Merus Power is participating in Energy ECS project to create secure and smart energy solutions for mobility in the future. The project has six use cases and Merus Power is leading in UC 3 for smart mobility with Emobility ...Rajattu käyttöoikeus / Restricted access / Tillgången är begränsad -
Performance Analysis of Classification Algorithms for Dry Bean Prediction
(2024)This thesis studies the efficacy of machine learning in dry bean classification. The Random Forest (RF), Optimized Forest (OF), and Logistic Model Tree (LMT) algorithms were evaluated using an openly accessible dataset ... -
Performance Comparison of One-Class Classifiers in Faulty Sanding Machine Detection Using Sound
(2023)Nowadays, product quality is a paramount concern in the modern machine manufacturing industry. Millions of dollars are being spent by modern machine manufacturing industries to maintain product quality. This expenditure ... -
Pneumonia Classification Model by Convolutional Neural Network
(2022)The purpose of this thesis is to train a model to recognize and classify X-ray images of pneumonia patients from those of normal people by approaches of convolutional neural networks in computer vision. This thesis introduces ... -
Pneumonia Detection and Diagnosis Formation in Chest X-ray Scans Using Localized Miniature Residual Convolution Neural Networks and GPT Integration
(2024)Chest radiography is one of the most preliminary forms of radiological investigation used globally. As such, it accounts for the gateway to detecting a plethora of pulmonary anomalies, the early diagnosis of which serves ... -
Possibilities in AI in customer care in the software business
(2024)Tekoälyn (AI) nopea kehitys tarjoaa uusia mahdollisuuksia tukipalvelun optimointiin. Tämän opinnäytetyön tavoitteena on analysoida AI:n potentiaalia asiakaspalvelutyöntekijöiden resurssien vapauttamiseksi ja asiakastyytyväisyyden ... -
Practical Attack and Defense Methods for Integrity of Deep Neural Networks in Digital Pathology Image Analysis Systems
(2024)Digital pathology has made huge strides in development over the past decade. The introduction of new technology brings with it huge potential in efficiency, accuracy, and cost benefits, but also new risks. From the point ... -
Predicting Acid Sulphate Soils in Finland’s Coastal Areas Using Deep Learning Fusion of Remote Sensing Map Tile Data
(2024)Acid Sulfate (AS) soils represent a significant ecological risk and are a major environmental concern, particularly in Finland, where they are recognized as one of the country’s most pressing environmental challenges. ... -
Predicting fine particulate matter levels in Finnish buildings
(2019)Fine particulate matter (PM 2.5 ) is considered one of the most harmful air pollutants. While a large proportion of the particles is originating from outdoor sources, people are mostly exposed while indoors. Predicting ...

















