We introduce AnyUp, a method for feature upsampling that can be applied to any vision feature at any resolution, without encoder-specific training. Existing learning-based upsamplers for features like ...
It appears that when rendering in spectral mode, for instance over 300nm --> 1100nm, that the spectral upsampling algorithm for RGB (for instance, for textures and/or HDRIs) does not produce any ...
Institute of Analytical Chemistry and Instrument for Life Science, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi’an ...
Abstract: A spatial upsampling method for the head-related transfer function (HRTF) using deep neural networks (DNNs), consisting of an autoencoder conditioned on the source position and frequency, is ...
To address the issues of missed detection and false detection during the defect inspection process of the PCB, an improved YOLOv7-based algorithm for PCB defect detection is proposed. Firstly, the ...
Machines learn to connect images and text by training on large datasets, where more data helps models recognize patterns and improve accuracy. Vision-language models (VLMs) rely on these datasets to ...
1 School of Computer and Control Engineering, Qiqihar University, Qiqihar, China 2 Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis, Qiqihaer University, Qiqihar, China ...
Background and objective: This study aimed to assess the impact of upsampling and downsampling techniques on the noise characteristics and similarity metrics of scintigraphic images in nuclear medical ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback