Essays about: "CoCo"

Showing result 11 - 15 of 49 essays containing the word CoCo.

1. 11. Investigation of real-time lightweight object detection models based on environmental parameters

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Dennis Persson; [2022]
   Keywords : object detection; convolutional neural network; environmental parameters;

   Abstract : As the world is moving towards a more digital world with the majority of people having tablets, smartphones and smart objects, solving real-world computational problems with handheld devices seems more common. Detection or tracking of objects using a camera is starting to be used in all kinds of fields, from self-driving cars, sorting items to x-rays, referenced in Introduction. READ MORE

3. 12. CNN-Based Methods for Tree Species Detection in UAV Images

   University essay from Linköpings universitet/Datorseende

   Author : Olle Sievers; [2022]
   Keywords : Machine Learning; CNN; UAV; Tree Species; Deep Learning; Tree Species Detection; Detection;

   Abstract : Unmanned aerial vehicles (UAVs) with high-resolution cameras are common in today’s society. Industries, such as the forestry industry, use drones to get a fast overview of tree populations. READ MORE

4. 13. Analysis of gradient-based optimization objective for robust machine learning classification

   University essay from Uppsala universitet/Institutionen för materialvetenskap

   Author : Gustav Fredrikson; [2022]
   Keywords : ;

   Abstract : The idea behind creating artificial intelligence extends far back in human history, founded on the idea of imitating human learning to better predict and make decisions. For over 70 years, scientists have worked on developing the rational ability in computers but are still a long way from the ultimate goal of creating a machine able to outperform humans in every intelligence-limited task. READ MORE

5. 14. Instance Segmentation of Multiclass Litter and Imbalanced Dataset Handling : A Deep Learning Model Comparison

   University essay from Linköpings universitet/Datorseende

   Author : Rolf Sievert; [2021]
   Keywords : Machine learning; Multiclass; Deep learning; Instance segmentation; Object segmentation; Iterative stratification; Mask R-CNN; DetectoRS; Imbalanced dataset; Classification; Detection; Segmentation; Litter; Trash; TACO; COCO; MMDetection; Multinomial; Cybercom; AI; Artificial intelligence; Land-based litter; Computer vision; Maskininlärning; Djupinlärning; Instanssegmentering; Objektsegmentering; Mask R-CNN; DetectoRS; Obalanserat dataset; Klassificering; Detektion; Segmentering; Skräp; TACO; COCO; MMDetection; Multinomial; Cybercom; AI; Artificiell intelligens; Datorseende;

   Abstract : Instance segmentation has a great potential for improving the current state of littering by autonomously detecting and segmenting different categories of litter. With this information, litter could, for example, be geotagged to aid litter pickers or to give precise locational information to unmanned vehicles for autonomous litter collection. READ MORE

6. 15. A test of GARCH models onCoCo bonds

   University essay from KTH/Skolan för industriell teknik och management (ITM)

   Author : JIMMY HENRIKSSON; [2021]
   Keywords : ARCH; GARCH; CoCo-bonds; Additional Tier-1; Volatility; Volatility forecasting; ARCH; GARCH; CoCo-obligationer; AT1; Volatilitet; Prediktion av volatilitet; Prognotisering av volatilitet;

   Abstract : This research investigates to what extent the ARCH model and the GARCH model forecasts one-day-ahead out-of-sample daily volatility (conditional variance) in European AT1 CoCo bonds compared to the Random Walk model. The research also investigates how different orders of ARCH and GARCH models affect the forecasting accuracy. READ MORE