Abstract
Flexible electronic devices, such as the typical thin-film transistors, are widely adopted in the area of sensors, displayers, wearable equipment, and such large-area applications, for their features of bending and stretching; additionally, in some applications of lower-resolution data converters recently, where a trend appears that implementing more parts of system with flexible devices to realize the fully flexible system. Nevertheless, relatively fewer works on the computation parts with flexible electronic devices are reported, due to their poor carrier mobility, which blocks the way to realize the fully flexible systems with uniform manufacturing process. In this paper, a novel circuit architecture for image processing accelerator using Oxide Thin-film transistor (TFT), which could realize real-time image pre-processing and classification in the analog domain, is proposed, where the performance and fault-tolerance of image signal processing is exploited. All of the computation is done in the analog signal domain and no clock signal is needed. Therefore, certain weaknesses of flexible electronic devices, such as low carrier mobility, could be remedied dramatically. In this paper, Simulations based on Oxide TFT device model have demonstrated that the flexible computing parts could perform 5 × 5 Gaussian convolution operation at a speed of 3.3 MOPS/s with the energy efficiency of 1.83 TOPS/J, and realize image classification at a speed of 10 k fps, with the energy efficiency of 5.25 GOPS/J, which means that the potential applications to realize real-time computing parts of complex algorithms with flexible electronic devices, as well as the future fully flexible systems containing sensors, data converters, energy suppliers, and real-time signal processing modules, all with flexible devices.
Highlights
With the advantages of transparency, softness, biocompatibility, etc., flexible electronic devices have been widely used in displaying and sensing fields [1]
As described in the Section 2.2.1, DoG is an approximation of Laplace of Gaussian (LoG) operator, which is usually used to detect the edge of objects in image with the advantages of high efficiency and low complexity
We have explored the computable circuit based on the relatively slower flexible Oxide thin-film transistor (TFT)
Summary
With the advantages of transparency, softness, biocompatibility, etc., flexible electronic devices have been widely used in displaying and sensing fields [1]. (ADC) [6], memory [7], sensors, and display [1,2] have been reported, the computation based on flexible devices is still an unsolved problem for the fully flexible system, especially for the complex algorithms with real-time processing requirements. 2.1 kHz. To sum up, the performance of TFT based digital circuit is not comparable with conventional silicon-based technology and is difficult to support the computation intensive real-time applications, such as the prevailing image signal processing and machine learning. High-speed and energy-efficient image processing based on flexible devices is realized, which is the key to implement the fully flexible system. The analysis of error and the ways to eliminate process variation are discussed in Section 5, and Section 6 concludes the paper
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