Avancerad sökning

Hittade 2 avhandlingar som matchar ovanstående sökkriterier.

1. 1. Deep Learning for Active Fire Detection Using Multi-Source Satellite Image Time Series

   Författare :Yu Zhao; Yifang Ban; Andrea Nascetti; Josephine Sullivan; Cartalis Constantinos; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Wildfire; Remote Sensing; Active Fire Detection; GOES-R ABI; Suomi-NPP VIIRS; Image Segmentation; Deep Learning; Gated Recurrent Units GRU ; Transformer.; Vilda Bränder; Fjärranalys; Aktiv Branddetektering; GOES- R ABI; Suomi-NPP VIIRS; Bildsegmentering; Djupinlärning; Gated Recurrent Units GRU ; Transformer; Geoinformatik; Geoinformatics;

   Sammanfattning : In recent years, climate change and human activities have caused increas- ing numbers of wildfires. Earth observation data with various spatial and temporal resolutions have shown great potential in detecting and monitoring wildfires. LÄS MER

3. 2. Machine Learning Approaches to Develop Weather Normalize Models for Urban Air Quality

   Författare :Chau Ngoc Phuong; Mengjie Han; Rasa Zalakeviciute; Ilias Thomas; Mario Salvador González Rodríguez; Högskolan Dalarna; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Weather Normalized Models WNMs ; Air Pollution; Data-Driven Modeling and Optimization; Deep Learning - Artificial Neural Network DL-ANN ; Machine Learning;

   Sammanfattning : According to the World Health Organization, almost all human population (99%) lives in 117 countries with over 6000 cities, where air pollutant concentration exceeds recommended thresholds. The most common, so-called criteria, air pollutants that affect human lives, are particulate matter (PM) and gas-phase (SO2, CO, NO2, O3 and others). LÄS MER