Content-Driven Associative Memories for Color Image Patterns

• Published in: IEEE transactions on cybernetics Vol. 48; no. 1; pp. 139 - 150
• Main Authors: Mingming Li, Ge, Shuzhi Sam, Tong Heng Lee
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Associative memory; Associative memory (AM); Basis functions; Color; Color imagery; content-driven association; Kernel; Kernels; large-scale color images; Neural networks; Noise tolerance; Object detection; Object recognition; partial radial basis function (PRBF) kernel; Radial basis function; Random noise; Robustness; Salience; salient object detection; Tensile stress; Tensors

This paper presents a novel content-driven associative memory (CDAM) to associate large-scale color images based on the subjects that represent the images' content. Compared to traditional associative memories, CDAM inherits their tolerance to random noise in images and possesses greater robust...