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Found 4 papers, 2 papers with code
Fast Autofocusing using Tiny Transformer Networks for Digital Holographic Microscopy
Tiny DL models are proposed and compared such as a tiny Vision Transformer (TViT), tiny VGG16 (TVGG) and a tiny Swin-Transfomer (TSwinT).
Convolutional Neural Network (CNN) vs Vision Transformer (ViT) for Digital Holography
In this paper, the determination of the distance is performed by Deep Learning (DL).
A Deep Learning Object Detection Method for an Efficient Clusters Initialization
However, the existing clustering techniques present significant limitations, from which is the dependability of their stability on the initialization parameters (e. g. number of clusters, centroids).
Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key
For the past few years, in the race between image steganography and steganalysis, deep learning has emerged as a very promising alternative to steganalyzer approaches based on rich image models combined with ensemble classifiers.
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