Essays about: "semantic segmentation"

Showing result 16 - 20 of 152 essays containing the words semantic segmentation.

1. 16. Evaluation of Ferroelectric Tunnel Junction memristor for in-memory computation in real world use cases

   University essay from Lunds universitet/Institutionen för elektro- och informationsteknik

   Author : Alec Guerin; Christos Papadopoulos; [2023]
   Keywords : FTJ; Ferroelectric Tunneling Junction; Analog in-memory computing; AIMC; Memristor; A.I.; AIHWKIT; Semantic segmentation; Natural Language Processing; NLP; Neuromorphic Computing; Matrix Vector Multiplication; Technology and Engineering;

   Abstract : Machine learning algorithms are experiencing unprecedented attention, but their inherent computational complexity leads to high energy consumption. However, a paradigm shift in computing methods has the potential to address the issue. READ MORE

3. 17. Land Use/Land Cover Classification From Satellite Remote Sensing Images Over Urban Areas in Sweden : An Investigative Multiclass, Multimodal and Spectral Transformation, Deep Learning Semantic Image Segmentation Study

   University essay from Linköpings universitet/Institutionen för datavetenskap

   Author : Oskar Aidantausta; Patrick Asman; [2023]
   Keywords : data fusion; deep learning; land use land cover classification; multiclass; multimodal; remote sensing; semantic segmentation; Sentinel satellite; spectral index; U-Net; Urban Atlas;

   Abstract : Remote Sensing (RS) technology provides valuable information about Earth by enabling an overview of the planet from above, making it a much-needed resource for many applications. Given the abundance of RS data and continued urbanisation, there is a need for efficient approaches to leverage RS data and its unique characteristics for the assessment and management of urban areas. READ MORE

4. 18. Skyline Delineation for Localization in Occluded Environments : Improved Skyline Delineation using Environmental Context from Deep Learning-based Semantic Segmentation

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

   Author : Kyle William Coble; [2023]
   Keywords : Skyline delineation; Skyline detection; Semantic segmentation; Terrain based navigation; Digital elevation models; Uncrewed surface vessel; Planetary exploration robots; Horisont avgränsning; Horisont upptäckt; Semantisk segmentering; Terrängbaserad navigering; Digitala höjdmodeller; Obemannat ytfartyg; Planetariska utforskningsrobotar;

   Abstract : This thesis addresses the problem of improving the delineation of skylines, also referred to as skyline detection, in occluded and challenging environments where existing skyline delineation methods may struggle or fail. Delineated skylines can be used in monocular camera localization methods by comparing delineated skylines to digital elevation model data to estimate a position based on known terrain. READ MORE

5. 19. Enhancement-basedSmall TargetDetection for InfraredImages

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

   Author : Yang Hanqi; [2023]
   Keywords : Infrared Images; Small targets; Dilated Convolution; Infraröda bilder; Små mål; Dilaterad konvolution;

   Abstract : Infrared small target detection is widely used in fields such as military and security. UNet, which is a classical semantic segmentation method proposed in 2015, has shown excellent performance and robustness. However, U-Net suffers from the problem of losing small targets in deep layers after multiple down-sampling operations. READ MORE

6. 20. Integration of Continual Learning and Semantic Segmentation in a vision system for mobile robotics

   University essay from Luleå tekniska universitet/Rymdteknik

   Author : Cristian David Echeverry Valencia; [2023]
   Keywords : Continual Learning; Progressive Neural Networks; mobile robotics; Computer Vision; Machine Learning; Semantic Segmentation;

   Abstract : Over the last decade, the integration of robots into various applications has seen significant advancements fueled by Machine Learning (ML) algorithms, particularly in autonomous and independent operations. While robots have become increasingly proficient in various tasks, object instance recognition, a fundamental component of real-world robotic interactions, has witnessed remarkable improvements in accuracy and robustness. READ MORE