Camouflaged object segmentation (COS) is a challenging task in computer vision where the objective is to recognize and precisely separate objects that blend in with their environment. Traditional ...

Abstract: Accurate mapping of oil palm plantations is crucial for sustainable management. Deep learning-based semantic segmentation technology, such as UNet and Deepl.ab, offers significant potential ...

Now that we have a good foundation on Image Segmentation, we will look into another model that is used for such tasks. U-Net, a convolutional neural network was proposed in 2015 in a paper by Olaf ...

This is an experimental project for Image-Segmentation of Ovarian-Tumor by using Tensorflow-Slightly-Flexible-UNet Model, which is a typical classic Tensorflow2 UNet implementation TensorflowUNet.py ...

This is an experimental project to detect Multiple-Myeloma from some pieces of tiled-images created from a large 4K image, by using our Tensorflow-Slightly-Flexible-UNet. Anubha Gupta, Ritu Gupta, ...

The accurate extraction of wheat lodging areas can provide important technical support for post-disaster yield loss assessment and lodging-resistant wheat breeding. At present, wheat lodging ...

Detection, diagnosis, and treatment of ophthalmic diseases depend on extraction of information (features and/or their dimensions) from the images. Deep learning (DL) model are crucial for the ...

Department of Electrical and Computer Engineering, University of Illinois at Urbana−Champaign, Urbana, Illinois 61801, United States Beckman Institute for Advanced Science and Technology, University ...

Hematoma volume (HV) is a significant diagnosis for determining the clinical stage and therapeutic approach for intracerebral hemorrhage (ICH). The aim of this study is to develop a robust deep ...