A feature-extraction and vector-generation VLSI has been developed for real-time image
recognition. An arrayed-shift-register architecture has been employed in conjunction with a …

A directional-edge-feature-based real-time image recognition system has been developed.
By employing a digital-pixel-sensor-embedded feature extraction VLSI processor, the delay …

Unique designs for CMOS analog arithmetic circuits are presented which perform addition
(V 1+ V 2), subtraction (V 2− V 1), add/invert−(V 1+ V 2), and multiply (V 1× V 2). The circuit …

Gradient descent learning algorithms, namely Back Propagation (BP), can significantly
increase the classification performance of Multi Layer Perceptrons adopting a local and …

In this paper, a global feature extraction very large scale integration (VLSI) architecture for
real-time object recognition is presented. To minimize the latency between capturing images …

The paper briefly reviews certain aspects of the biological visual system and presents a
smart vision sensor for the detection of higher-level features. The visual system processes …

A mixed-mode very large scale integration (VLSI) processor for acoustic transient
classification performs a running correlation between a time-frequency decomposed analog …

Human posture recognition is gaining increasing attention nowadays, especially in the area
of assisted living and elderly care. The aim of this thesis is to explore the design and …

Supervised learning algorithms (ie Back Propagation algorithms, BP) are reliable and widely
adopted for real world applications. Among supervised algorithms, stochastic ones (eg …

The goal of this research is to explore the design and implementation of a hardware
accelerated highlyefficient engine for the categorization of objects, using asynchronous …