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1. 1. Optimizing Flight Ranking:A Machine Learning Approach : Applying Machine Learning to Upgrade Flight Sorting and User Experience

   University essay from KTH/Hälsoinformatik och logistik

   Author : Habib Jabeli; [2024]
   Keywords : Machine Learning; Flight Comparison; Flygresor.se; Neural Networks; Flight Ranking; Random Forest; XGBoost;

   Abstract : Flygresor.se, a leading flight comparison platform, uses machine learning to rankflights based on their likelihood of being clicked. The main goal of this project was toimprove this flight sorting to obtain a better user experience. The platform's existingmodel is based on a neural network approach and a limited set of features. READ MORE

3. 2. Learning a Grasp Prediction Model for Forestry Applications

   University essay from Umeå universitet/Institutionen för fysik

   Author : Elias Olofsson; [2024]
   Keywords : Forwarder; Autonomous grasping; Deep learning; Multibody dynamics; Convolutional neural network;

   Abstract : Since the advent of machine learning and machine vision methods, progress has been made in tackling the long-standing research question of autonomous grasping of arbitrary objects using robotic end-effectors. Building on these efforts, we focus on a subset of the general grasping problem concerning the automation of a forwarder. READ MORE

4. 3. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving

   University essay from Uppsala universitet/Signaler och system

   Author : Jonas Wedén; [2024]
   Keywords : Machine Learning; ML; Reinforcement Learning; RL; Neural Network; Deep Learning; Autonomous Vehicle; Vehicle; CARLA; Convolutional Neural Network; CNN; Precisit; Q-learning; Deep Q-learning; DQN;

   Abstract : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. READ MORE

5. 4. 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

6. 5. Enhancement of a Power Line Information System by Combining BIM and LiDAR Data

   University essay from KTH/Lantmäteri – fastighetsvetenskap och geodesi

   Author : Daniel Wollberg; [2024]
   Keywords : GIS; BIM; FME; CloudCompare; GIS; BIM; FME; CloudCompare;

   Abstract : With the great ongoing energy transition in Sweden, Svenska Kraftnät (SVK) sees a huge need for investment in the Swedish transmission network and supporting IT- systems.  SVK has a great amount of collected laser data over the electric power transmission network however this data does not contain any semantic attribution that can be analyzed on broader information systems. READ MORE