
Mennel, L. et al. Ultrafast machine vision with 2D material neural network image sensors. Nature 579, 62–66 (2020).
Jang, H. et al. In-sensor optoelectronic computing using electrostatically doped silicon. Nat. Electron. 5, 519–525 (2022).
Chai, Y. In-sensor computing for machine vision. Nature 579, 32–33 (2020).
Choi, C. et al. Curved neuromorphic image sensor array using a MoS2–organic heterostructure inspired by the human visual recognition system. Nat. Commun. 11, 5934 (2020).
Zhou, F. et al. Optoelectronic resistive random access memory for neuromorphic vision sensors. Nat. Nanotechnol. 14, 776–782 (2019).
Seung, H. et al. Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns. Sci. Adv. 8, eabq3101 (2022).
Jayachandran, D. et al. A low-power biomimetic collision detector based on an in-memory molybdenum disulfide photodetector. Nat. Electron. 3, 646–655 (2020).
Chai, Y. Silicon photodiodes that multiply. Nat. Electron. 5, 483–484 (2022).
Zhou, F. & Chai, Y. Near-sensor and in-sensor computing. Nat. Electron. 3, 664–671 (2020).
Li, X. et al. Power-efficient neural network with artificial dendrites. Nat. Nanotechnol. 15, 776–782 (2020).
Wan, T. et al. In-sensor computing: materials, devices, and integration technologies. Adv. Mater. 9, 2203830 (2022).
Kim, M. et al. An aquatic-vision-inspired camera based on a monocentric lens and a silicon nanorod photodiode array. Nat. Electron. 3, 546–553 (2020).
Simonyan, K. & Zisserman, A. Two-stream convolutional networks for action recognition in videos. Adv. Neural Inf. Process Syst. 27, 568–576 (2014).
Ye, H. et al. Evaluating two-stream CNN for video classification. In Proceedings of the 5th ACM on International Conference on Multimedia Retrieval 435–442 (Association for Computing Machinery, 2015).
Liao, F. et al. Bioinspired in-sensor visual adaptation for accurate perception. Nat. Electron. 5, 84–91 (2022).
Jung, D. et al. Highly conductive and elastic nanomembrane for skin electronics. Science 373, 1022–1026 (2021).
Song, Y. M. et al. Digital cameras with designs inspired by the arthropod eye. Nature 497, 95–99 (2013).
Lee, M. et al. An amphibious artificial vision system with a panoramic visual field. Nat. Electron. 5, 452–459 (2022).
Ayers, J., Davis, J. L. & Rudolph, A. Neurotechnology for Biomimetic Robots (MIT Press, 2002).
Webb, B. Robots with insect brains. Science 368, 244–245 (2020).
de Ruyter van Steveninck, R. & Laughlin, S. The rate of information transfer at graded-potential synapses. Nature 379, 642–645 (1996).
Tuthill, J. C., Nern, A., Holtz, S. L., Rubin, G. M. & Reiser, M. B. Contributions of the 12 neuron classes in the fly lamina to motion vision. Neuron 79, 128–140 (2013).
Zheng, L. et al. Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: I dynamics. PLoS ONE 4, e4307 (2009).
Miall, R. The flicker fusion frequencies of six laboratory insects, and the response of the compound eye to mains fluorescent ‘ripple’. Physiol. Entomol. 3, 99–106 (1978).
Kelly, D. & Wilson, H. Human flicker sensitivity: two stages of retinal diffusion. Science 202, 896–899 (1978).
Uusitalo, R. & Weckstrom, M. Potentiation in the first visual synapse of the fly compound eye. J. Neurophysiol. 83, 2103–2112 (2000).
Nikolaev, A. et al. Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: II mechanisms. PLoS ONE 4, e4306 (2009).
Hu, W., Wang, T., Wang, X. & Han, J. Ih channels control feedback regulation from amacrine cells to photoreceptors. PLoS Biol. 13, e1002115 (2015).
Laughlin, S. B., de Ruyter van Steveninck, R. R. & Anderson, J. C. The metabolic cost of neural information. Nat. Neurosci. 1, 36–41 (1998).
Juusola, M., French, A. S., Uusitalo, R. O. & Weckström, M. Information processing by graded-potential transmission through tonically active synapses. Trends Neurosci. 19, 292–297 (1996).
Schuetzenberger, A. & Borst, A. Seeing natural images through the eye of a fly with remote focusing two-photon microscopy. Iscience 23, 101170 (2020).
Liu, K. et al. An optoelectronic synapse based on α-In2Se3 with controllable temporal dynamics for multimode and multiscale reservoir computing. Nat. Electron. 5, 761–773 (2022).
Warland, D., Landolfa, M., Miller, J. P. & Bialek, W. in Analysis and Modeling of Neural Systems (ed Eeckman, F. H.) 327–333 (Springer, 1992).
Jiang, J. et al. Defect engineering for modulating the trap states in 2D photoconductors. Adv. Mater. 30, 1804332 (2018).
- SEO Powered Content & PR Distribution. Get Amplified Today.
- Platoblockchain. Web3 Metaverse Intelligence. Knowledge Amplified. Access Here.
- Minting the Future w Adryenn Ashley. Access Here.
- Source: https://www.nature.com/articles/s41565-023-01379-2
- ][p
- 1
- 10
- 11
- 1996
- 1998
- 20
- 2014
- 2018
- 2019
- 2020
- 2021
- 2022
- 28
- 2D
- 7
- 8
- 9
- a
- access
- accurate
- ACM
- Action
- active
- adaptation
- AL
- an
- and
- Array
- article
- artificial
- Association
- At
- based
- brains
- by
- camera
- cameras
- Cells
- channels
- classes
- classification
- click
- CNN
- Compound
- computing
- Conference
- contributions
- control
- Cost
- Davis
- designs
- Devices
- Diffusion
- digital
- DOT
- dynamics
- ed
- Electronics
- Engineering
- Ether (ETH)
- evaluating
- eye
- feedback
- field
- First
- focusing
- For
- French
- from
- fusion
- highly
- http
- HTTPS
- human
- i
- image
- images
- improves
- in
- information
- inspired
- integration
- International
- laboratory
- Lens
- LINK
- machine
- machine vision
- machinery
- material
- materials
- Memory
- Microscopy
- Miller
- MIT
- modeling
- motion
- Multimedia
- Natural
- Nature
- network
- networks
- Neural
- neural network
- Neurons
- of
- on
- patterns
- perception
- plato
- Plato Data Intelligence
- PlatoData
- press
- process
- processing
- Quantum
- Quantum dot
- random
- Rate
- recognition
- Regulation
- remote
- representation
- response
- robots
- s
- seeing
- Sensitivity
- sensors
- Silicon
- SIX
- Skin
- stages
- States
- Synapse
- Synapses
- system
- Technologies
- that
- The
- Through
- to
- transfer
- using
- Video
- Videos
- vision
- Visual recognition
- visualization
- W
- Wilson
- with
- X
- zephyrnet