Contribute to yasharth2004/Image-classification-using-resNet34 development by creating an account on GitHub.

We report a semi-supervised Vision Transformer (ViT) framework for automated reflection high energy electron diffraction (RHEED) image classification of ferroelectric nitride (ScAlN) materials grown ...

This notebook explores and compares various Explainable AI (XAI) techniques—LIME, Anchors, and SHAP—to explain the predictions made by a pre-trained ResNet34 model for image classification.

In image classification tasks using ViTs and CNNs, the softmax function is commonly employed to represent the output as a probability value. However, these outputs are often poorly calibrated, making ...

Satellite image classification is a crucial component in remote sensing applications, facilitating the automated analysis of land cover and land use patterns. This research explores the effectiveness ...

Specifically, it can reduce the workload of network architecture design and reduce the process of a large number of verification experiments [9]. The method based on the automatic design of ...

7 School of Computing, Shanmugha Arts, Science, Technology & Research Academy Deemed University, Thanjavur, India Brain tumor classification plays a niche role in medical prognosis and effective ...