C&EN

Leveraging Deep Learning to Address Diagnostic Challenges with Insufficient Image Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In recent AI-driven disease diagnosis, the success of models has depended mainly on ...
IEEE

Teacher-Student Instance-level Adversarial Augmentation for Single Domain Generalized Medical Image Segmentation

Abstract: Recently, single-source domain generalization (SDG) has gained popularity in medical image segmentation. As a prominent technique, adversarial image augmentation technique can generate ...
Frontiers

RCTNet: Residual conv-attention transformer network for corn hyperspectral image classification

Classifying corn varieties presents a significant challenge due to the high-dimensional characteristics of hyperspectral images and the complexity of feature extraction, which hinder progress in ...
Scientific Research Publishing

Nelson, J. (2020) The Importance of Blur as an Image Augmentation Technique. Roboflow Blog.

ABSTRACT: This paper focuses on the use of YOLOv12 for the early detection of Sexually Transmitted Infections, which are a global public health challenge. YOLOv12 is a deep-learning model released on ...
Scientific Research Publishing

Impact of Data Augmentation Technique on Automatic Brain Tumor Detection Using ResNet CNN ()

1 Doctoral School of Mathematics and Computer Science, Dakar, Senegal. 2 Research Laboratory in Digital Science and Technology, Multinational Higher School of Telecommunications, Dakar, Senegal. The ...
GitHub

Add Additional Transformations for Image Augmentation, better Finetuning on Small Datasets

While RF-DETR performs excellently out-of-the-box with large labeled datasets, I have been hitting a wall on fine-tuning runs for RF-DETR on smaller datasets (~1000 images with 1-5 objects per image).
GitHub

Several Problems when using Keras Image Augmentation Layers to Augment Images and Masks for a Semantic Segmentation Dataset

In the following, I will try to tell you a bit of my “story” about how I read through the various layers and (partly outdated) tutorials on image augmentation for semantic segmentation, what problems ...