Comparative Analysis of Image Enhancement Techniques for Brain Tumor Segmentation: Contrast, Histogram, and Hybrid Approaches

no code implementations • 8 Apr 2024 • Shoffan Saifullah, Andri Pranolo, Rafał Dreżewski

This study systematically investigates the impact of image enhancement techniques on Convolutional Neural Network (CNN)-based Brain Tumor Segmentation, focusing on Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and their hybrid variations.

Brain Tumor Segmentation Image Enhancement +2

Nondestructive chicken egg fertility detection using CNN-transfer learning algorithms

no code implementations • 28 Sep 2023 • Shoffan Saifullah, Rafal Drezewski, Anton Yudhana, Andri Pranolo, Wilis Kaswijanti, Andiko Putro Suryotomo, Seno Aji Putra, Alin Khaliduzzaman, Anton Satria Prabuwono, Nathalie Japkowicz

In testing set, it achieved an accuracy of 0. 98, a sensitivity of 1 for detecting fertile eggs, and a specificity of 0. 96 for identifying non-fertile eggs.

Specificity Transfer Learning

Optimized Three Deep Learning Models Based-PSO Hyperparameters for Beijing PM2.5 Prediction

no code implementations • 10 Jun 2023 • Andri Pranolo, Yingchi Mao, Aji Prasetya Wibawa, Agung Bella Putra Utama, Felix Andika Dwiyanto

Deep learning is a machine learning approach that produces excellent performance in various applications, including natural language processing, image identification, and forecasting.

Management Metaheuristic Optimization