Feb 13, 2023 · One-sentence Summary: We study what can be inferred about a single-image super resolution network by looking at its output images.
The paper focused on the single-image super-resolution task and considered a wide choice of model architecture, dataset, scale, loss and seed. The paper studied ...
This is the official implementation of our TMLR paper fingerprints of super resolution networks. Installation. Requirements.
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Dec 10, 2020 · To find a solution for recovering pore information from low-resolution fingerprints, we adopt a joint learning-based approach that combines both ...
This paper addressed the problem of multi-frame image super resolution and implementation to fingerprint image. The use of computers in fingerprints ...
This paper proposes a method for super-resolving low-resolution fingerprints based on deep dictionary learning. ... super-resolution and pore detection networks.
Feb 15, 2024 · An unsupervised learning method for 3D fingerprint super-resolution is proposed, denoted as CycleSR. ... networks using only LR test images. The ...
Aug 18, 2022 · In this paper, we address the challenging task of estimating the distance between different users in a Millimeter Wave (mmWave) massive ...
neural networks for matching fingerprints for authentication. Direct optical ... network is as high as the noise level of the features will allow for ...
Feb 26, 2024 · We demonstrate SEMORE on simulations and diverse raw super-resolution data: time-resolved insulin aggregates, and published data of dSTORM ...