IEEE

Enhancing Coffee Leaf Disease Classification via Active Learning and Diverse Sample Selection

Abstract: Accurate classification of coffee leaf diseases is essential for early intervention and improved crop yield. However, training deep learning models for this task often requires large labeled ...
GitHub

Fuzzy Equivalence–Driven Feature Selection with Constrained Sigmoid Similarity for Interpretable Supervised Learning

The code includes the core methodology, experimental results generation, and the script used to produce Table 4 from the manuscript. The framework is designed to be label-agnostic during similarity ...
Frontiers

Self-supervised transfer learning for few-shot classification on marine plankton images

The classification of marine plankton images is of great significance in ecological studies and environmental monitoring. In practical applications, plankton image classification faces several ...
IEEE

Feature Selection With Maximal Relevance and Minimal Supervised Redundancy

Abstract: Feature selection (FS) for classification is crucial for large-scale images and bio-microarray data using machine learning. It is challenging to select informative features from ...