Hybrid Pyramid / Neural Network Vision System,

Abstract

We have discussed with the NEL the types and variety of images and targets needed to evaluate our technology for aiding image analysts in real-world applications. We decided on the problem of detecting bomb-damaged structures. We have since visited the NEL to use the Directed-Search Testbed for selecting the positive examples for training and testing. We are in the process of preparing the data at Sarnoff for training. Training should begin early in June. NIDL funding is expected for applying the HPNN technology to two separate problems in breast-cancer screening: (1) Finding microcalcifications (evidence of tumors) in mammograms. This is a continuation of our previous work which reduced the false-positive rate obtained by the Rossman laboratory of University of Chicago by a factor of two. (2) Detecting masses in mammograms. The Joint Warfare Analysis Center has made some additional progress (to that described in our last report) in evaluating the HPNN technology. They have applied it to their own imagery, and report that in the initial tests it works well.

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Document Details

Document Type
Technical Report
Publication Date
May 31, 1996
Accession Number
ADA309558

Entities

People

  • John C. Pearson

Organizations

  • Sarnoff Corporation

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Breast Cancer
  • Cancer Screening
  • Contractors
  • Contracts
  • Governments
  • Neoplasms
  • Neural Networks
  • Training
  • Universities

Readers

  • Computer Vision.
  • Oncology and Biomarker-Based Cancer Detection.
  • Technical Research and Report Writing.

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks