Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Since the images and masks of the original Drone Images are very large (3.8K to 4.4K pixels width), we adopted the following Divide-and-Conquer Strategy for building our segmentation model. 1. Tiled ...

Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

Abstract: Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep ...

As shown below, the inferred masks predicted by our segmentation model trained on the PNG dataset appear similar to the ground truth masks, but lack precision in some areas. To improve segmentation ...

Abstract: Genetic Programming (GP) is a promising evolutionary machine learning technique for image classification, known for its ability to evolve flexible, effective, and interpretable models.

Introduction: Breast cancer (BC) is a malignant neoplasm that originates in the mammary gland’s cellular structures and remains one of the most prevalent cancers among women, ranking second in ...