IEEE

Generative Data-Driven Dynamic Deep Learning Classifier Selection for Hyperspectral Image Classification

Abstract: Deep learning has emerged as a critical paradigm in hyperspectral image (HSI) classification, addressing the inherent challenges posed by high-dimensional data and limited labeled samples.
Digital Trends

Gemini’s Deep Research tool may soon learn to pull sources from your Gmail and Drive

Why is this important? This upgrade will allow users to pull source material directly from their Gmail, Drive, or Chat, eliminating the need to manually download and upload files. Why should I care?
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
GitHub

deep-learning-project

White Blood Cell Classification is a deep learning project built with Python, TensorFlow, and Keras that classifies five types of WBCs from microscopic images using a CNN model. With advanced image ...
IEEE

From Data to Knowledge: A Knowledge Graph-Guided Framework to Deep Learning for Hyperspectral Image Classification

Abstract: Recent advances in deep learning have significantly improved hyperspectral image (HSI) classification. However, deep learning models for HSI classification typically rely on one-hot labels, ...