Sökning: "neural network"
Visar resultat 21 - 25 av 2313 uppsatser innehållade orden neural network.
21. Planet-NeRF : Neural Radiance Fields for 3D Reconstruction on Satellite Imagery in Season Changing Environments
Master-uppsats, Linköpings universitet/DatorseendeSammanfattning : This thesis investigates the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer vision, per- forms in predicting seasonal variations across different months. LÄS MER
22. Using search based methods for beamforming
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknikSammanfattning : In accommodating the growing global demand for wireless, Multi-User Multiple-Input and Multiple-Output (MU-MIMO) systems have been identified as the key technology. In such systems, a transmitting basestation serves several users simultaneously, increasing the network capacity. LÄS MER
23. Leveraging Large Language Models for Firm-Intelligence: A RAG Framework Approach
Magister-uppsats, Lunds universitet/Statistiska institutionenSammanfattning : In the wake of OpenAI's release of ChatGPT in November 2022, powered by the 175 billion parameter neural network GPT-3, the potential applications of Large Language Models (LLMs) in various sectors have become evident. One such application lies in hedge funds and trading desks where knowledge sharing is paramount. LÄS MER
24. Classifying femur fractures using federated learning
Master-uppsats, Linköpings universitet/Statistik och maskininlärningSammanfattning : The rarity and subtle radiographic features of atypical femoral fractures (AFF) make it difficult to distinguish radiologically from normal femoral fractures (NFF). Compared with NFF, AFF has subtle radiological features and is associated with the long-term use of bisphosphonates for the treatment of osteoporosis. LÄS MER
25. The Impact of Deep Neural Network Pruning on the Hyperparameter Performance Space: An Empirical Study
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : With the continued growth of deep learning models in terms of size and computational requirements, the need for efficient models for deployment on resource-constrained devices becomes crucial. Structured pruning has emerged as a proven method to speed up models and reduce computational requirements. LÄS MER