The authors describe the negative fuse, an analog model which encourages boundary completion in early vision regularization algorithms. This algorithm is an extension of the successful implementation of line processes in analog VLSI using the resistive fuse (Harris et al.). The negative fuse provides for true negative resistance regions for the enhancement of edges, making long connected edges more likely to occur. This model has a natural mapping into inexpensive, fast, low-power analog hardware. The authors discuss the performance of a negative fuse element fabricated in VLSI and show simulations of network performance on digitized camera images
In the last ten years, significant progress has been made in understanding the first steps in visual...
A system for color correction has been designed, built, and tested successfully; the essential comp...
Abstract—Cellular Nonlinear Networks (CNN) establish a theoretical framework in which programmable f...
The detection of discontinuities in motion, intensity, color, and depth is a well-studied but diffic...
The detection of discontinuities in motion, intensity, color, and depth is a well-studied but diffic...
Analog models provide a novel framework for understanding and developing algorithms for computer vis...
The resistive-fuse network is a well-known image segmen-tation processing model in which image edges...
The authors have designed and tested a one-dimensional 64 pixel, analog CMOS VLSI chip which localiz...
To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" the...
This thesis concerns the use of nonlinear resistive networks for solving ill-posed problems in compu...
This paper presents the theory behind a model for a two-stage analog network for edge detection and ...
Two digital LSI implementation methods for nonlinear resistive networks are proposed; one is for pix...
We describe two successfully working, analog VLSI vision circuits that move beyond pixel-based early...
Segmentation is a basic problem in computer vision. The tiny-tanh network, a continuous-time network...
To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" th...
In the last ten years, significant progress has been made in understanding the first steps in visual...
A system for color correction has been designed, built, and tested successfully; the essential comp...
Abstract—Cellular Nonlinear Networks (CNN) establish a theoretical framework in which programmable f...
The detection of discontinuities in motion, intensity, color, and depth is a well-studied but diffic...
The detection of discontinuities in motion, intensity, color, and depth is a well-studied but diffic...
Analog models provide a novel framework for understanding and developing algorithms for computer vis...
The resistive-fuse network is a well-known image segmen-tation processing model in which image edges...
The authors have designed and tested a one-dimensional 64 pixel, analog CMOS VLSI chip which localiz...
To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" the...
This thesis concerns the use of nonlinear resistive networks for solving ill-posed problems in compu...
This paper presents the theory behind a model for a two-stage analog network for edge detection and ...
Two digital LSI implementation methods for nonlinear resistive networks are proposed; one is for pix...
We describe two successfully working, analog VLSI vision circuits that move beyond pixel-based early...
Segmentation is a basic problem in computer vision. The tiny-tanh network, a continuous-time network...
To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" th...
In the last ten years, significant progress has been made in understanding the first steps in visual...
A system for color correction has been designed, built, and tested successfully; the essential comp...
Abstract—Cellular Nonlinear Networks (CNN) establish a theoretical framework in which programmable f...