Sökning: "träffsäkerhet"
Visar resultat 1 - 5 av 304 uppsatser innehållade ordet träffsäkerhet.
1. Comparison of Hebbian Learning and Backpropagation for Image Classification in Convolutional Neural Networks
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Current commonly used image recognition convolutional neural networks share some similarities with the human brain. However, the differences are many and the well established backpropagation learning algorithm is not biologically plausible. LÄS MER
2. Comparing machine learning algorithms for detecting behavioural anomalies
Uppsats för yrkesexamina på avancerad nivå, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background. Attempted intrusions at companies, either from an insider threat orotherwise, is increasing in frequency. Most commonly used is static analysis and filters to stop specific attacks. LÄS MER
3. Hit song analysis on the Swedish music market : An exploration of hit song classification
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Assessing hit song potential is a challenge in the music industry. The question of what song to promote, which song to release first and whether or not it will succeed has always been an issue for stakeholders in the music business. The ability to statistically evaluate hit song potential is a growing field with several studies exploring the topic. LÄS MER
4. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. LÄS MER
5. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition
Master-uppsats, KTH/Mekatronik och inbyggda styrsystemSammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER