✦ LIBER ✦

Reconstruction and recognition of face and digit images using autoencoders

✍ Scribed by Chun Chet Tan; C. Eswaran

Publisher: Springer-Verlag
Year: 2010
Tongue: English
Weight: 576 KB
Volume: 19
Category: Article
ISSN: 0941-0643
DOI: 10.1007/s00521-010-0378-4

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Knowledge-based contextual recognition a

Knowledge-based contextual recognition and sieving of digital images

✍ P. Bottoni; P. Mussio; M. Protti; R. Schettini 📂 Article 📅 1989 🏛 Elsevier Science 🌐 English ⚖ 677 KB

Integrated multilevel image fusion and m

Integrated multilevel image fusion and match score fusion of visible and infrared face images for robust face recognition

✍ Richa Singh; Mayank Vatsa; Afzel Noore 📂 Article 📅 2008 🏛 Elsevier Science 🌐 English ⚖ 595 KB

Volumetric Reconstruction of Objects and

Volumetric Reconstruction of Objects and Scenes Using Range Images

✍ D.L. Elsner; R.T. Whitaker; M.A. Abidi 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 380 KB

This paper reviews volumetric methods for fusing sets of range images to create 3D models of objects or scenes. It also presents a new reconstruction method, which is a hybrid that combines several desirable aspects of techniques discussed in the literature. The proposed reconstruction method projec

Numerical reconstruction and twin-image

Numerical reconstruction and twin-image suppression using an off-axis Fresnel digital hologram

✍ G.L. Chen; C.Y. Lin; M.K. Kuo; C.C. Chang 📂 Article 📅 2008 🏛 Springer 🌐 English ⚖ 440 KB

Reconstruction and analysis of multi-pos

Reconstruction and analysis of multi-pose face images based on nonlinear dimensionality reduction

✍ Changshui Zhang; Jun Wang; Nanyuan Zhao; David Zhang 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 948 KB

Locally linear embedding (LLE) is a nonlinear dimensionality reduction method proposed recently. It can reveal the intrinsic distribution of data, which cannot be provided by classical linear dimensionality reduction methods. The application of LLE, however, is limited because of its lack of a param

Small metal nanoparticle recognition usi

Small metal nanoparticle recognition using digital image analysis and high resolution electron microscopy

✍ A.B Flores; L.A Robles; M.O Arias; J.A Ascencio 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 735 KB

In this paper, we present a system developed to identify metal nanoparticles at different orientations, using digital image processing and analysis. The correct identification is important in nanotechnology, where it is possible to build structures for different purposes at the nanometric level. The