ArticleMicromachines2022
Design of a Miniaturized Wide-Angle Fisheye Lens Based on Deep Learning and Optimization Techniques.
Article in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Secondary Imaging Architecture for Fast and Ultra-Wide LWIR Optics with Low Rectilinear Distortion.Sensors (Basel, Switzerland) · 2026Article
- Power quality disturbance identification using hybrid deep learning in renewable energy systems.Scientific reports · 2025Article
- AI-Based Metamaterial Design.ACS applied materials & interfaces · 2024Review
- Design and Development of an Ultraviolet All-Sky Imaging System.Sensors (Basel, Switzerland) · 2023Article
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Authors and funding
3 authors.
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Abstract
This paper presents the optimization design of a miniaturized five-element wide-angle fisheye lens using a deep learning algorithm. Zemax optical design software was used to simulate and optimize the wide-angle fisheye lens. A deep learning algorithm helped to find the best combination of different lens materials. We first used six lens elements as an initial configuration to design miniaturized wide-angle fisheye lenses using the optimization process. The optical system components were gradually decreased to five lens elements. Both OKP4HT and polymethyl methacrylate (PMMA) plastic aspheric lenses were selected to replace the second spherical glass lens in the original design. We propose two types of wide-angle fisheye lens designs with four spherical lenses and one aspheric lens. The results for these designs indicated a viewing angle of 174°, a total length of less than 15 mm, a spot size of less than 6 μm, lateral color within ±1 μm, field curvature within ±0.02 mm, and F-θ distortion of ±3.5%. In addition, the MTF value was larger than 0.4 at the spatial frequency of 100 cycles/mm.
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