i-Tac inversely designs 3D-printed elastomers by fitting mixture-design response surface models and applying multi-objective optimization to achieve target optical and mechanical properties in one fabrication step.
The beer-lambert law,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
UDehaze-iT is a lightweight deep network that enhances underwater images by implicitly estimating depth and deriving transmission via learnable Beer-Lambert attenuation coefficients, achieving competitive results on UIEB and UFO-120 with 0.9M parameters.
citing papers explorer
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i-Tac: Inverse Design of 3D-Printed Tactile Elastomers with Scalable and Tunable Optical and Mechanical Properties
i-Tac inversely designs 3D-printed elastomers by fitting mixture-design response surface models and applying multi-objective optimization to achieve target optical and mechanical properties in one fabrication step.
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An Underwater Dehazing Network with Implicit Transmission Estimation
UDehaze-iT is a lightweight deep network that enhances underwater images by implicitly estimating depth and deriving transmission via learnable Beer-Lambert attenuation coefficients, achieving competitive results on UIEB and UFO-120 with 0.9M parameters.