- author = "Astro Teller and Manuela Veloso",
- title = "Algorithm Evolution for Face Recognition: What Makes a Picture Difficult",
- booktitle = "International Conference on Evolutionary Computation",
- year = "1995",
- volume = "2",
- pages = "608--613",
- address = "Perth, Australia",
- publisher_address = "Piscataway, NJ, USA",
- month = "1--3 " # dec,
- publisher = "IEEE Press",
- keywords = "genetic algorithms, genetic programming, memory, computer vision, Face recognition, Machine learning, Computer vision, Image databases, Neural networks, ANN, Machine learning algorithms, Computer science, Evolutionary computation, Humans",
- ISBN = "0-7803-2759-4",
-
URL = "
http://www.cs.cmu.edu/afs/cs/usr/astro/public/papers/icecFinal.ps",
-
URL = "
http://citeseer.ist.psu.edu/558916.html",
-
DOI = "
doi:10.1109/ICEC.1995.487453",
- size = "6 pages",
- abstract = "One of the classic problems in computer vision is the face recognition problem. In general this problem can take on a wide variety of forms, but the most common face recognition problem is Who is this a picture of? Evolution computation has, in the past, been applied indirectly to this problem through techniques like learning Neural Networks. This paper introduces a Genetic Programming style approach to learning algorithms that directly investigate face images and are coordinated into a face recognition system. Through a series of experiments, we will show that evolved algorithms can accomplish the face recognition task. We will also highlight several pitfalls and misconceptions surrounding face recognition as a learning problem.",
-
notes = "ICEC-95 PADO also known as \cite{487453}
conference details at broken Aug 2024 http://ciips.ee.uwa.edu.au/~dorota/icnn95.html",
