Computational and Neural Network Models for the Analysis of Visual Texture

Abstract

The grant supported research efforts in two main research questions: (1) How do we segment and estimate the slant/tilt of natural scenes with highly irregular textures, using both biological and non-biological computing architectures; and (2) How do we design -machine perception and action systems and learning mechanisms that can improve their performance through repeated feedback and interaction with their environment? Section 2 describes the research and publications relating to the slant/tilt and segmentation problem. Section 3 describes research and publications using developmental psychological and machine learning frameworks for learning visuomotor tasks. Finally, Section 4 summarizes the two Ph.D dissertations in the Department of Computer and Information Science made possible with AFOSR support.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 13, 1992
Accession Number
ADA258166

Entities

People

  • G. Gerstein
  • R. Bajcsy

Organizations

  • University of Pennsylvania

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence Software
  • Computational Neuroscience
  • Computational Science
  • Computations
  • Computer Vision
  • Computers
  • Data Sets
  • Information Science
  • Machine Learning
  • Machine Perception
  • Neural Networks
  • Psychology
  • Reinforcement Learning
  • Robotics
  • Simulations
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Parallel and Distributed Computing.
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks