2023
DOI: 10.1039/d3tc01883k
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Evolution of natural eyes and biomimetic imaging devices for effective image acquisition

Abstract: In the natural evolutionary process, biological creatures have developed diverse visual structures apt for their habitational environments. These natural vision structures have inspired the development of artificial vision systems. These...

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Cited by 10 publications
(5 citation statements)
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“…Visual information, in particular, accounts for a significant portion of the surrounding data, leading to the development of artificial vision systems. 816 The camera, composed of multiple lenses and a planar image sensor, has become a fundamental design of the artificial vision system. With the recent advances of electronics and mechanics, modern machines and robots carry out multiple tasks via diverse sensing systems, including vision.…”
Section: Artificial Vision Systemsmentioning
confidence: 99%
See 1 more Smart Citation
“…Visual information, in particular, accounts for a significant portion of the surrounding data, leading to the development of artificial vision systems. 816 The camera, composed of multiple lenses and a planar image sensor, has become a fundamental design of the artificial vision system. With the recent advances of electronics and mechanics, modern machines and robots carry out multiple tasks via diverse sensing systems, including vision.…”
Section: Artificial Vision Systemsmentioning
confidence: 99%
“…Sensing ability is a crucial factor to most animals for survival that requires tons of external information from visual, auditory, and tactile cues. Visual information, in particular, accounts for a significant portion of the surrounding data, leading to the development of artificial vision systems . The camera, composed of multiple lenses and a planar image sensor, has become a fundamental design of the artificial vision system.…”
Section: Representative Human-centric Applications Of Flexible and St...mentioning
confidence: 99%
“…Meanwhile, natural vision systems, from biological eyes to visual recognition systems, which oftentimes show excellent performance and simple structure by surpassing those of man-made vision systems, offer promising insights to address the inefficiencies of conventional devices (Figure b). , However, to mimic and implement key structural and functional features of the biological vision systems, it is required to realize curved form factors and neuromorphic characteristics in the imaging system. However, these cannot be achieved by using traditional rigid and flat CMOS image sensors. , Thereby, mechanically deformable nanomaterials (e.g., silicon (Si) nanomembranes, ,, two-dimensional (2D) materials, amorphous oxide semiconductors, , and nanocrystals (quantum dots (QDs) , and halide perovskites )) and unconventional device technologies (e.g., flexible devices with kirigami designs, ,, devices using stretchable interconnections, and intrinsically stretchable devices , ) have emerged as promising technical solutions for the development of multifunctional high-performance bioinspired artificial vision systems.…”
Section: Introductionmentioning
confidence: 99%
“…Meanwhile, natural vision systems, from biological eyes to visual recognition systems, which oftentimes show excellent performance and simple structure by surpassing those of manmade vision systems, offer promising insights to address the inefficiencies of conventional devices (Figure 2b). 26,32 However, to mimic and implement key structural and functional features of the biological vision systems, it is required to realize curved form factors 33−35 and neuromorphic characteristics 36−38 in the imaging system. However, these cannot be achieved by using traditional rigid and flat CMOS image sensors.…”
Section: Introductionmentioning
confidence: 99%
“…Bioinspired artificial vision research has yielded a multitude of unconventional imaging systems that model structural and functional characteristics of the diverse eyes in nature ( 1 5 ). These artificial visions have shown fascinating performances and potential, particularly beneficial for next-generation mobile robotics.…”
Section: Introductionmentioning
confidence: 99%