Essays about: "efficient training"

Showing result 1 - 5 of 304 essays containing the words efficient training.

1. 1. Deep reinforcement learning for automated building climate control

   University essay from Linköpings universitet/Institutionen för datavetenskap

   Author : Erik Snällfot; Martin Hörnberg; [2024]
   Keywords : Machine Learning; Reinforcement Learning; Deep Learning; Deep Reinforcement Learning; Building Control; Control System;

   Abstract : The building sector is the single largest contributor to greenhouse gas emissions, making it a natural focal point for reducing energy consumption. More efficient use of energy is also becoming increasingly important for property managers as global energy prices are skyrocketing. READ MORE

3. 2. Virtual H&E Staining Using PLS Microscopy and Neural Networks

   University essay from Lunds universitet/Matematik LTH

   Author : Sally Vizins; Hanna Råhnängen; [2024]
   Keywords : Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

   Abstract : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. READ MORE

4. 3. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Khalid El Yaacoub; [2024]
   Keywords : Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Abstract : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. READ MORE

5. 4. Image Quality Assessment Pipeline and Semi-Automated Annotation method for Synthetic Data

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Liam Le Tran; Edina Dedovic; [2023-10-24]
   Keywords : Facial Expression Recognition; FACS; Action Units; styleGAN2-ada; synthetic data; Image Quality Assessment; Multi-stage Pre-training; Pipeline Processing; Semi-automated Human Annotation;

   Abstract : Predicting human emotions through facial expression, particularly in relation to medication field such as clinical trial settings, has garnered scientific interest in recent years due to significant understanding of the impact of treatment on emotions and social functioning. This thesis aims to improve performance of a FER model using large scale of synthetic data. READ MORE

6. 5. Decoding the surface code using graph neural networks

   University essay from Göteborgs universitet / Institutionen för fysik

   Author : Moritz Lange; [2023-10-17]
   Keywords : ;

   Abstract : Quantum error correction is essential to achieve fault-tolerant quantum computation in the presence of noisy qubits. Among the most promising approaches to quantum error correction is the surface code, thanks to a scalable two-dimensional architecture, only nearest-neighbor interactions, and a high error threshold. Decoding the surface code, i.e. READ MORE