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Showing result 1 - 5 of 670 essays matching the above criteria.
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1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. READ MORE
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2. 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)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
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3. Heart rate estimation from wrist-PPG signals in activity by deep learning methods
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. READ MORE
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4. Implementations and evaluation of machine learning algorithms on a microcontroller unit for myoelectric prosthesis control
University essay from Lunds universitet/Avdelningen för Biomedicinsk teknikAbstract : Using a microcontroller unit to implement different machine learning algorithms for myoelectric prosthesis control is currently feasible. Still there are hardware and timing constraints that need to be accounted for. READ MORE
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5. Machine Learning model applied to Reactor Dynamics
University essay from KTH/FysikAbstract : This project’s idea revolved around utilizing the most recent techniques in MachineLearning, Neural Networks, and Data processing to construct a model to be used asa tool to determine stability during core design work. This goal will be achieved bycollecting distribution profiles describing the core state from different steady statesin five burn-up cycles in a reactor to serve as the dataset for training the model. READ MORE