Sökning: "Binär Klassificering"
Visar resultat 1 - 5 av 40 uppsatser innehållade orden Binär Klassificering.
1. Impact of Cell Type Selection on Binary Classification of Cervical Cancer using Convolutional Neural Networks : A Compatibility Analysis of Herlev and SIPaKMeD
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cervical cancer is one of the most common forms of cancer today, affecting women worldwide. Machine learning classifiers could potentially be utilized to aid in the diagnosis of cervical cancer, making screening more cost-effective. LÄS MER
2. An Evaluation of Classical and Quantum Kernels for Machine Learning Classifiers
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Quantum computing is an emerging field with potential applications in machine learning. This research project aimed to compare the performance of a quantum kernel to that of a classical kernel in machine learning binary classification tasks. LÄS MER
3. Quality Assuring an Image Data Pipeline with Transfer Learning : Using Computer Vision Methodologies
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen Vi3Sammanfattning : The computer vision field has taken big steps forwards and the amount of models and datasets that are being released is increasing. A large number of contemporary models are the result of extensive training sessions on massive datasets, reflecting a significant investment of time and computational resources. LÄS MER
4. Time Series Analysis and Binary Classification in a Car-Sharing Service : Application of data-driven methods for analysing trends, seasonality, residuals and prediction of user demand
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Researchers have estimated a 20-percentage point increase in the world’s population residing in urban areas between 2011 and 2050. The increase in denser cities results in opportunities and challenges. Two of the challenges concern sustainability and mobility. LÄS MER
5. Detecting gastrointestinal abnormalities with binary classification of the Kvasir-Capsule dataset : A TensorFlow deep learning study
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : The early discovery of gastrointestinal (GI) disorders can significantly decrease the fatality rate of severe afflictions. Video capsule endoscopy (VCE) is a technique that produces an eight hour long recording of the GI tract that needs to be manually reviewed. LÄS MER