Parallelizing analog in-sensor visual processing with arrays of gate-tunable silicon photodetectors
সংরক্ষণ করুন:
| প্রকাশিত: | Nature Communications vol. 16, no. 1 (2025), p. 4728 |
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| প্রকাশিত: |
Nature Publishing Group
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | Citation/Abstract Full Text - PDF |
| ট্যাগগুলো: |
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| 003 | UK-CbPIL | ||
| 022 | |a 2041-1723 | ||
| 024 | 7 | |a 10.1038/s41467-025-60006-x |2 doi | |
| 035 | |a 3207696895 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 145839 |2 nlm | ||
| 245 | 1 | |a Parallelizing analog in-sensor visual processing with arrays of gate-tunable silicon photodetectors | |
| 260 | |b Nature Publishing Group |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a In-sensor processing of dynamic and static information of visual objects avoids exchanging redundant data between physically separated sensing and computing units, holding promise for computer vision hardware. To this end, gate-tunable photodetectors, if built in a highly scalable array form, would lend themselves to large-scale in-sensor visual processing because of their potential in volume production and hence, parallel operation. Here we present two scalable in-sensor visual processing arrays based on dual-gate silicon photodiodes, enabling parallelized event sensing and edge detection, respectively. Both arrays are built in CMOS compatible processes and operated with zero static power. Furthermore, their bipolar analog output captures the amplitude of event-driven light changes and the spatial convolution of optical power densities at the device level, a feature that helps boost their performance in classifying dynamic motions and static images. Capable of processing both temporal and spatial visual information, these retinomorphic arrays suggest a path towards large-scale in-sensor visual processing systems for high-throughput computer vision.Xiong et al. report two scalable in-sensor visual processing arrays based on dual-gate silicon photodiodes, parallelizing the temporal and spatial information analysis. The bipolar analog output captures the amplitude of event-driven light changes, facilitating the classification of dynamic motions and static images. | |
| 653 | |a Silicon | ||
| 653 | |a Data analysis | ||
| 653 | |a Amplitudes | ||
| 653 | |a Spatial analysis | ||
| 653 | |a Spatial data | ||
| 653 | |a Classification | ||
| 653 | |a Computer vision | ||
| 653 | |a Sensors | ||
| 653 | |a Sensor arrays | ||
| 653 | |a Photodiodes | ||
| 653 | |a Information processing | ||
| 653 | |a Arrays | ||
| 653 | |a Photometers | ||
| 653 | |a Parallel operation | ||
| 653 | |a Edge detection | ||
| 773 | 0 | |t Nature Communications |g vol. 16, no. 1 (2025), p. 4728 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3207696895/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3207696895/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |