-h show this help -i input Input image or folder. Default: inputs/whole_imgs -o output Output folder. Default: results -v version GFPGAN model version. Option: 1 | 1.2 | 1.3. Default: 1.3 -s upscale The final upsampling scale of the image. Default: 2 -bg_upsampler background up...
In 2020, Jia Shukai significantly improved the performance of thyroid ultrasound image segmentation by introducing a feature pyramid module, a multi-scale input strategy, and an attention mechanism in the U-net network framework [11]. To raise the resolution of the input ultrasound image, Lin et...
That is valuable and you should check the image that way, but it does not tell you everything about how an image will look in print. For one thing, the final printed image will not be seen at 100% magnification, people will see the print at View > Actual Size. Also, it ...
Unsupervised image segmentation is a technique that divides an image into distinct regions or objects without prior labeling. This approach offers flexibility and adaptability to various types of image data. Particularly for large datasets, it eliminates
Cryo-EM structure of the CORVET complex and its specific subunits Fig. 1: Purification and cryo-EM structure of the yeast CORVET complex. Full size image Fig. 2: Interactions of CORVET functional subunits with the core of the complex.
This paper reviews the current state of the art in artificial intelligence (AI) technologies and applications in the context of the creative industries. A
Considering the enormous scale of the Leshan Giant Buddha (with 1021 ushnisha on the head), each deterioration inspection is a formidable task. The detection capability of this model can be continuously applied to future inspection work, significantly reducing the workload of cultural heritage ...
Added sanitizing of : and / just before first dummy inference ScaleMul.onnx.zip Before onnx2tf \ -i ScaleMul.onnx \ -kat onnx__Mul_0 onnx__Mul_1 \ -cind "onnx::Mul_0" pos.npy \ -cind "onnx::Mul_1" pos_scales.npy \ -cotof After onnx2tf \ -i ScaleMul.onnx \ ...
The segmentation of retinal vasculature from eye fundus images is a fundamental task in retinal image analysis. Over recent years, increasingly complex approaches based on sophisticated Convolutional Neural Network architectures have been pushing perform
Combination therapy has gained popularity in cancer treatment as it enhances the treatment efficacy and overcomes drug resistance. Although machine learning (ML) techniques have become an indispensable tool for discovering new drug combinations, the data