Sökning: "computer vision"
Visar resultat 1 - 5 av 378 uppsatser innehållade orden computer vision.
- Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik
Sammanfattning : Depth estimation using stereo images is an important task in many computer vision applications. A stereo camera contains two image sensors that observe the scene from slightly different viewpoints, making it possible to find the depth of the scene. An active stereo camera also uses a laser projector that projects a pattern into the scene. LÄS MER
- Master-uppsats, Lunds universitet/Ergonomi och aerosolteknologi
Sammanfattning : The purpose of this thesis is two-fold. The first is to investigate if cutting edge technology can be used to enhance the life for people with visual impairments. The second is to provide a simple example of how the design process can look from the beginning to a finished Hi-Fi prototype. LÄS MER
- Master-uppsats, Linköpings universitet/Datorseende; Linköpings universitet/Datorseende
Sammanfattning : Finding disparity maps between stereo images is a well studied topic within computer vision. While both classical and machine learning approaches exist in the literature, they frequently struggle to correctly solve the disparity in regions with low texture, sharp edges or occlusions. LÄS MER
- Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap
Sammanfattning : Context. Image enhancement algorithms can be used to enhance the visual effects of images in the field of human vision. So can image enhancement algorithms be used in the field of computer vision? The convolutional neural network, as the most powerful image classifier at present, has excellent performance in the field of image recognition. LÄS MER
- Master-uppsats, Lunds universitet/Institutionen för astronomi och teoretisk fysik
Sammanfattning : In recent years, Deep Learning has proven to be an outstanding tool in the field of computer vision showing promising results in different fields such as the analysis of medical images, obstacle detection for self-driving cars, automatic image caption generation, etc. In the case of Archaeology, the adoption of these methods in the detection of archaeological structures from aerial images has been slower than in other fields. LÄS MER