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http://cio.repositorioinstitucional.mx/jspui/handle/1002/1099| STEREO VISION BASED SLAM IN DYNAMIC OUTDOOR ENVIRONMENTS USING DEEP LEARNING | |
| Daniela Esparza | |
| Gerardo Flores | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| SLAM Dynamic Environment Outdoor Environment Semantic Segmentation Neural Networks Stereo Vision | |
| "This thesis presents a Simultaneous Localization and Mapping (SLAM) system focused on dynamic environments using convolutional neural networks. The proposed system employs a stereo camera as the input of the SLAM for the acquisition of left and right images and depth map. The neural network is used for object detection and segmentation to avoid erroneous maps and wrong system location. The main job of the neural network is to find out objects within the scene, and to use its features for dynamic detection. Moreover, the processing time of the proposed system is fast and can run in real-time being able to run in outdoor and indoor environments." | |
| 2019-10 | |
| Tesis de maestría | |
| Inglés | |
| León, Guanajuato | |
| Público en general | |
| Martínez Esparza, (2019). "Stereo Vision Based SLAM in Dynamic Outdoor Environments Using Deep Learning". Tesis de Maestría en Optomecatrónica. Centro de Investigaciones en Óptica, A.C. León, Guanajuato. 72 pp. | |
| INTELIGENCIA ARTIFICIAL | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | MAESTRIA EN OPTOMECATRÓNICA |
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| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| 17698.pdf | Texto completo/Full text | 2.72 MB | Adobe PDF | Visualizar/Abrir |