Essays about: "future state vision"

Showing result 21 - 25 of 72 essays containing the words future state vision.

1. 21. FPGA Implementation of Feature Matching in ORB-SLAM2

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

   Author : Hannah Lindström; [2022]
   Keywords : Autonomous navigation; SLAM; Feature matching; FPGA; ORB; Heterogeneous binary tree; Technology and Engineering;

   Abstract : Simultaneous Localization And Mapping (SLAM) is an important component in solving the problem of autonomous navigation — allowing machines such as selfdriving cars and mobile robots to find their way in the world without human instruction. Though there is a steadily growing body of literature in the field of SLAM, far fewer works currently address using hardware acceleration to speed up this computationally heavy task. READ MORE

3. 22. Semantic segmentation of off-road scenery on embedded hardware using transfer learning

   University essay from KTH/Mekatronik

   Author : Filip Elander; [2021]
   Keywords : Semantic Segmentation; forestry navigation; Deep Neural Network; autonomous navigation; residual neural network; Convolutional neural network; Semantisk Segmentering; Autonom Terrängnavigering; Residuala Nätverk; Konvolutionellt Neuralt Nätverk; Autonom navigering;

   Abstract : Real-time semantic scene understanding is a challenging computer vision task for autonomous vehicles. A limited amount of research has been done regarding forestry and off-road scene understanding, as the industry focuses on urban and on-road applications. READ MORE

4. 23. 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

5. 24. Real-time hand segmentation using deep learning

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

   Author : Federico Favia; [2021]
   Keywords : Hand Segmentation; Semantic Segmentation; Deep Learning; Convolutional Neural Networks; Real-time; Augmented Reality; Embedded Devices; Dataset; Transfer Learning; Handsegmentering; Semantisk Segmentering; Djupinlärning; Konvolutionsneurala Nätverk; Realtid; Förstärkt Verklighet; Inbäddade Enheter; Datauppsättning; Transferlärning;

   Abstract : Hand segmentation is a fundamental part of many computer vision systems aimed at gesture recognition or hand tracking. In particular, augmented reality solutions need a very accurate gesture analysis system in order to satisfy the end consumers in an appropriate manner. Therefore the hand segmentation step is critical. READ MORE

6. 25. The Road To Urban Streets : The redevelopment of transport infrastructure in relation to the Swedish planning process

   University essay from KTH/Urbana och regionala studier

   Author : Ellen McManus; Albin Bellander; [2021]
   Keywords : sustainable transport planning; socio-technical transitions; obduracy; urban streets; densification;

   Abstract : Urban planning needs to address the future role of transport infrastructure in cities. Due to previous planning ideals, our cities consist of transport networks that stand in conflict with ambitions to create dense and multifunctional urban environments, decrease pollution, and create safe urban space. READ MORE