Sökning: "spatial attention"
Visar resultat 1 - 5 av 170 uppsatser innehållade orden spatial attention.
1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER
2. Multicriteria Evaluation in Real Estate Land-use Suitability Analysis: The case of Volos, Greece
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : The integration of Geographic Information Systems (GIS) into real estate analysis has long been considered an interesting interdisciplinary pursuit, but has yet to become mainstream. Despite the increasing academic focus over the last twenty years, this endeavour has mostly been approached from the scientific side of Geography. LÄS MER
3. Expansive Lighting
Magister-uppsats, KTH/LjusdesignSammanfattning : The composition of visual landscapes significantly impacts the utilization of eye features, consequently reflected in perception. As an outstanding species, human perception holds profound planetary consequences, directly influencing experience and behavior. LÄS MER
4. Biodiversity Monitoring Using Machine Learning for Animal Detection and Tracking
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : As an important indicator of biodiversity and ecological environment in a region, the number and distribution of animals has been given more and more attention by agencies such as nature reserves, wetland parks, and animal protection supervision departments. To protect biodiversity, we need to be able to detect and track the movement of animals to understand which animals are visiting the space. LÄS MER
5. Using Machine Learning to Optimize Near-Earth Object Sighting Data at the Golden Ears Observatory
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This research project focuses on improving Near-Earth Object (NEO) detection using advanced machine learning techniques, particularly Vision Transformers (ViTs). The study addresses challenges such as noise, limited data, and class imbalance. LÄS MER