All‐In‐One Hardware Devices with Event‐Based Vision Sensor Arrays for Image Sensing, Computing, and Learning
Sen Zhang,
Pingdan Xiao,
Xitong Hong
et al.
Abstract:Metal oxide semiconductors (MOSs) are considered as potential candidates for the low‐cost, large‐area fabrication of flexible optoelectronic devices. However, the current optoelectronic devices based on MOSs are limited to unidirectional photoresponse, which constrains the performance of MOSs‐based vision sensors for artificial vision systems. Herein, for the first time, a flexible artificial vision system integrated with optical perception, computation, and learning functionalities is demonstrated using SnO o… Show more
“…A pair of X-ray optical pulses (79.38 mGy/s, pulse width = 2 s) are applied to the device, and the PPF effect of the device is shown schematically in Figure 4b. Their PPF indexes can be calculated by A 2 /A 1 = 1 + C 1 exp(−Δt/τ 1 ) + C 2 exp(−Δt/τ 2 ), 52 where C 1 and C 2 are the initial amplitudes of the fast and slow relaxation processes, and τ 1 and τ 2 are the This result is also consistent with the variation trend of the response speed of the three devices (Figure 4a). The reason for this phenomenon may be due to the more obvious persistent photoconductivity (PPC) effect with the increase in oxygen flux during the growth of Ga 2 O 3 films.…”
Section: ■ Results and Discussionsupporting
confidence: 80%
“…A pair of X-ray optical pulses (79.38 mGy/s, pulse width = 2 s) are applied to the device, and the PPF effect of the device is shown schematically in Figure b. Their PPF indexes can be calculated by A 2 / A 1 = 1 + C 1 exp(−Δ t /τ 1 ) + C 2 exp(−Δ t /τ 2 ), where C 1 and C 2 are the initial amplitudes of the fast and slow relaxation processes, and τ 1 and τ 2 are the time constants of the two processes. The interval of the two pulses is changed from 1 to 50 s, the PPF indexes of the three devices are measured separately, and the results and trends are shown in Figure c.…”
Recognition and judgment of X-ray computed tomography (CT) images play a crucial role in medical diagnosis and disease prevention. However, the storage and calculation of the X-ray imaging system applied in the traditional CT diagnosis is separate, and the pathological judgment is based on doctors' experience, which will affect the timeliness and accuracy of decision-making. In this paper, a simplestructured reservoir computing network (RC) is proposed based on Ga 2 O 3 X-ray optical synaptic devices to recognize medical skeletal CT images with high accuracy. Through oxygen vacancy engineering, Ga 2 O 3 X-ray optical synaptic devices with adjustable photocurrent gain and a persistent photoconductivity effect were obtained. By using the Ga 2 O 3 X-ray optical synaptic device as a reservoir, we constructed an RC network for medical skeletal CT diagnosis and verified its image recognition capability using the MNIST data set with an accuracy of 78.08%. In the elbow skeletal CT image recognition task, the recognition rate is as high as 100%. This work constructs a simple-structured RC network for X-ray image recognition, which is of great significance in applications in medical fields.
“…A pair of X-ray optical pulses (79.38 mGy/s, pulse width = 2 s) are applied to the device, and the PPF effect of the device is shown schematically in Figure 4b. Their PPF indexes can be calculated by A 2 /A 1 = 1 + C 1 exp(−Δt/τ 1 ) + C 2 exp(−Δt/τ 2 ), 52 where C 1 and C 2 are the initial amplitudes of the fast and slow relaxation processes, and τ 1 and τ 2 are the This result is also consistent with the variation trend of the response speed of the three devices (Figure 4a). The reason for this phenomenon may be due to the more obvious persistent photoconductivity (PPC) effect with the increase in oxygen flux during the growth of Ga 2 O 3 films.…”
Section: ■ Results and Discussionsupporting
confidence: 80%
“…A pair of X-ray optical pulses (79.38 mGy/s, pulse width = 2 s) are applied to the device, and the PPF effect of the device is shown schematically in Figure b. Their PPF indexes can be calculated by A 2 / A 1 = 1 + C 1 exp(−Δ t /τ 1 ) + C 2 exp(−Δ t /τ 2 ), where C 1 and C 2 are the initial amplitudes of the fast and slow relaxation processes, and τ 1 and τ 2 are the time constants of the two processes. The interval of the two pulses is changed from 1 to 50 s, the PPF indexes of the three devices are measured separately, and the results and trends are shown in Figure c.…”
Recognition and judgment of X-ray computed tomography (CT) images play a crucial role in medical diagnosis and disease prevention. However, the storage and calculation of the X-ray imaging system applied in the traditional CT diagnosis is separate, and the pathological judgment is based on doctors' experience, which will affect the timeliness and accuracy of decision-making. In this paper, a simplestructured reservoir computing network (RC) is proposed based on Ga 2 O 3 X-ray optical synaptic devices to recognize medical skeletal CT images with high accuracy. Through oxygen vacancy engineering, Ga 2 O 3 X-ray optical synaptic devices with adjustable photocurrent gain and a persistent photoconductivity effect were obtained. By using the Ga 2 O 3 X-ray optical synaptic device as a reservoir, we constructed an RC network for medical skeletal CT diagnosis and verified its image recognition capability using the MNIST data set with an accuracy of 78.08%. In the elbow skeletal CT image recognition task, the recognition rate is as high as 100%. This work constructs a simple-structured RC network for X-ray image recognition, which is of great significance in applications in medical fields.
“…In addition, an effective strategy is to rely on the modulating impact of the gate voltage on the channel in the phototransistor. Simultaneously, by employing the heterostructure (WSe 2 /h-BN/Al 2 O 3 , Cl 2 –NDI/PBI-1, PdSe 2 /MoTe 2 ) or channel with bipolar conductivity (SnO/HfO 2 , DTT-8/TFT-CN), the phototransistor is capable of exhibiting a bidirectional photoresponse when the gate voltage is altered. The effectiveness of this strategy is contingent upon modulating the application of light with the gate voltage, hence increasing the complexity of the device construction.…”
“…Inspired by biological vision systems, retina-like photodetectors that mimic the structural and functional features of human retinas have attracted widespread attention. − It not only makes it possible for some blind people to regain vision but also enhances human vision by multifunctional photodetectors such as the retina. , Importantly, the bioinspired photodetectors are required to be similar to the curvature of the human retinas to perceive external light signals. , There are primarily two strategies to construct these photodetectors containing micronano devices. One is the direct manufacturing of micronano devices on curved support substrates, which requires addressing significant technical challenges. − Another method possesses two steps; the first step is to place initially manufactured micronano devices on a flexible planar substrate.…”
Stretchable organic phototransistor arrays have potential applications in artificial visual systems due to their capacity to perceive ultraweak light across a broad spectrum. Ensuring uniform mechanical and electrical performance of individual devices within these arrays requires semiconductor films with large-area scale, well-defined orientation, and stretchability. However, the progress of stretchable phototransistors is primarily impeded by their limited electrical properties and photodetection capabilities. Herein, wafer-scale and well-oriented semiconductor films were successfully prepared using a solution shearing process. The electrical properties and photodetection capabilities were optimized by improving the polymer chain alignment. Furthermore, a stretchable 10 × 10 transistor array with high device uniformity was fabricated, demonstrating excellent mechanical robustness and photosensitive imaging ability. These arrays based on highly stretchable and well-oriented wafer-scale semiconductor films have great application potential in the field of electronic eye and artificial visual systems.
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