Sökning: "novel object recognition."

Visar resultat 1 - 5 av 25 avhandlingar innehållade orden novel object recognition..

1. 1. Embodied Visual Object Recognition

   Författare :Marcus Wallenberg; Per-Erik Forssén; Michael Felsberg; Aleš Ude; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; object recognition; machine learning; computer vision;

   Sammanfattning : Object recognition is a skill we as humans often take for granted. Due to our formidable object learning, recognition and generalisation skills, it is sometimes hard to see the multitude of obstacles that need to be overcome in order to replicate this skill in an artificial system. LÄS MER

3. 2. Components of Embodied Visual Object Recognition : Object Perception and Learning on a Robotic Platform

   Författare :Marcus Wallenberg; Per-Erik Forssén; Mårten Björkman; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; computer vision; object recognition; stereo vision; classification;

   Sammanfattning : Object recognition is a skill we as humans often take for granted. Due to our formidable object learning, recognition and generalisation skills, it is sometimes hard to see the multitude of obstacles that need to be overcome in order to replicate this skill in an artificial system. LÄS MER

4. 3. Exploring Biologically-Inspired Interactive Networks for Object Recognition

   Författare :Mohammad Saifullah; Arne Jönsson; Rita Kovordányi; Christian Balkenius; Linköpings universitet; []
   Nyckelord :Interactive neural networks; Biologically-Inspired models; Visual attention; Object recognition.; TECHNOLOGY; TEKNIKVETENSKAP;

   Sammanfattning : This thesis deals with biologically-inspired interactive neural networks for the task of object recognition. Such networks offer an interesting alternative approach to traditional image processing techniques. Although the networks are very powerful classification tools, they are difficult to handle due to their bidirectional interactivity. LÄS MER

5. 4. Studies in Semantic Modeling of Real-World Objects using Perceptual Anchoring

   Författare :Andreas Persson; Amy Loutfi; Alessandro Saffiotti; Severin Lemaignan; Örebro universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Perceptual Anchoring; Semantic World Modeling; Sensor-Driven Acquisition of Data; Object Recognition; Object Classification; Symbol Grounding; Probabilistic Object Tracking;

   Sammanfattning : Autonomous agents, situated in real-world scenarios, need to maintain consonance between the perceived world (through sensory capabilities) and their internal representation of the world in the form of symbolic knowledge. An approach for modeling such representations of objects is through the concept of perceptual anchoring, which, by definition, handles the problem of creating and maintaining, in time and space, the correspondence between symbols and sensor data that refer to the same physical object in the external world. LÄS MER

7. 5. Visual Representations and Models: From Latent SVM to Deep Learning

   Författare :Hossein Azizpour; Stefan Carlsson; Barbara Caputo; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Vision; Machine Learning; Artificial Intelligence; Deep Learning; Learning Representation; Deformable Part Models; Discriminative Latent Variable Models; Convolutional Networks; Object Recognition; Object Detection; Computer Science; Datalogi;

   Sammanfattning : Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. LÄS MER