Analytics Insight

Best Deep Learning Books to Read in 2026

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

Deep learning-based classification of multiple fundus diseases using ultra-widefield images

1 Department of ophthalmology, JiuJiang City Key Laboratory of Cell Therapy, Jiujiang No. 1 People’s Hospital, JiuJiang, Jiangxi, China 2 Department of Otolaryngology, The Seventh Affiliated Hospital, ...
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, ...
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 ...
GitHub

Uncertainty Quantification for Deep Learning in Sleep Apnea Detection

This repository contains the Python code for the Master's Thesis: "Uncertainty Quantification for Deep Learning in Sleep Apnea Detection: A Comparative Evaluation of Monte Carlo Dropout and Deep ...
Frontiers

GLN-LRF: global learning network based on large receptive fields for hyperspectral image classification

Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...