IEEE

Distribution Learning Based on Evolutionary Algorithm-Assisted Deep Neural Networks for Imbalanced Image Classification

Abstract: Imbalanced image classification faces critical challenges in balancing the quality and diversity of synthetic minority samples. This article proposes the improved estimation distribution ...
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 ...
Scientific Research Publishing

Comparative Research in Sentiment Analysis Using Machine Learning Technique ()

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...
Frontiers

Synergizing BRDF correction and deep learning for enhanced crop classification in GF-1 WFV imagery

Crop classification is a key task in remote sensing, supporting agricultural monitoring, food security, and ecological management (Ding et al., 2023; Gentry et al., 2025). The Gaofen-1 (GF-1) ...
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, ...