Sökning: "Neural Network interpretability"
Visar resultat 1 - 5 av 22 uppsatser innehållade orden Neural Network interpretability.
1. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. LÄS MER
2. Towards gradient faithfulness and beyond
Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : The riveting interplay of industrialization, informalization, and exponential technological growth of recent years has shifted the attention from classical machine learning techniques to more sophisticated deep learning approaches; yet its intrinsic black-box nature has been impeding its widespread adoption in transparency-critical operations. In this rapidly evolving landscape, where the symbiotic relationship between research and practical applications has never been more interwoven, the contribution of this paper is twofold: advancing gradient faithfulness of CAM methods and exploring new frontiers beyond it. LÄS MER
3. Automated Interpretation of Lung Ultrasound for COVID-19 and Tuberculosis diagnosis
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : BACKGROUND. Early and accurate detection of infectious respiratory diseases like COVID-19 and tuberculosis (TB) plays a crucial role in effective management and the reduction of preventable mortality. LÄS MER
4. Convolution-compacted visiontransformers forprediction of localwall heat flux atmultiple Prandtlnumbers in turbulentchannel flow
Master-uppsats, KTH/Skolan för teknikvetenskap (SCI)Sammanfattning : Predicting wall heat flux accurately in wall-bounded turbulent flows is critical for a variety of engineering applications, including thermal management systems and energy-efficient designs. Traditional methods, which rely on expensive numerical simulations, are hampered by increasing complexity and extremly high computation cost. LÄS MER
5. Evaluating Process Mining Techniques on PACS Command Usage Data : Exploring common process mining techniques and evaluating their applicability on PACS event log data for domain-specific workflow analysis
Master-uppsats, Linköpings universitet/Institutionen för datavetenskapSammanfattning : Many software companies today collect command usage data by monitoring and logging user interactions within their applications. This is not always utilised to its full potential, but with the use of state-of-the-art process mining techniques, this command usage log data can be used to gain insights about the users' workflows. LÄS MER