Sökning: "state of the art information"
Visar resultat 1 - 5 av 418 uppsatser innehållade orden state of the art information.
1. Offshore Wind Farms in Norway : A Spatial Multi-Criteria Analysis for Optimal Site Location
Master-uppsats, KTH/Hållbar utveckling, miljövetenskap och teknikSammanfattning : Recognizing the imperative transition towards renewable energy sources to combat climate change, this study explores the outlooks for offshore wind power in Norway, a country endowed with extensive coastlines and favourable wind conditions. The thesis sets out to support decision-making processes by synthesizing contemporary research and applying context-specific insights to the southern half of the Norwegian economic zone (NEZ) into a comprehensive Spatial-Multi-criteria Analysis (SMCA). LÄS MER
2. Modulating Depth Map Features to Estimate 3D Human Pose via Multi-Task Variational Autoencoders
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Human pose estimation (HPE) constitutes a fundamental problem within the domain of computer vision, finding applications in diverse fields like motion analysis and human-computer interaction. This paper introduces innovative methodologies aimed at enhancing the accuracy and robustness of 3D joint estimation. LÄS MER
3. Time-based Key for Coverless Audio Steganography: A Proposed Behavioral Method to Increase Capacity
Uppsats för yrkesexamina på avancerad nivå, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background. Coverless steganography is a relatively unexplored area of steganography where the message is not embedded into a cover media. Instead the message is derived from one or several properties already existing in the carrier media. This renders steganalysis methods used for traditional steganography useless. LÄS MER
4. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER
5. Assessing the Efficiency of COLMAP, DROID-SLAM, and NeRF-SLAM in 3D Road Scene Reconstruction
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : 3D reconstruction is a field in computer vision which has evolved rapidly as a result of the recent advancements in deep learning. As 3D reconstruction pipelines now can run in real-time, this has opened up new possibilities for teams developing Advanced Driver Assistance Systems (ADAS), which rely on the camera system of the vehicle to enhance the safety and driving experience. LÄS MER