Scientific Research Publishing

Hybrid Deep Learning Model for Breast Cancer Classification in Low-Middle Income Countries: A MobileNetV2 and Cubic SVM ()

Breast cancer is one of the major causes of female death in any part of the world, and the burden is highly ...
Scientific Research Publishing

UWB NLOS Signal Recognition Based on Deep Learning ()

However, in indoor environments, non-line-of-sight (NLOS) signals significantly degrade the ranging performance of UWB ...

Deep learning model enables accurate and scalable drug-drug interaction prediction

Managing complex medical conditions often requires the simultaneous use of multiple different drugs, referred to as polypharmacy. While necessary, this significantly increases the risk of drug-drug ...
EurekAlert!

Jeonbuk National University researchers develop DDINet for accurate and scalable drug-drug interaction prediction

Drug-drug interactions (DDI) can cause adverse drug reactions during the co-administration of multiple drugs, necessitating accurate and scalable prediction tools. While deep learning models have ...
Hosted on MSN

Learning to count in binary

A light and accessible introduction to the binary number system, showing how computers represent numbers using just zeros and ones. Trump slams interpreter before Latin American leaders in Doral ...
Frontiers

Chlamy_ChloroPred: a deep learning-based, highly accurate binary classifier for chloroplast protein prediction in the model microalga, Chlamydomonas reinhardtii, with potential ...

The chloroplast, a living relic of an ancient endosymbiotic interaction between a microalga and a microbe and the principal subcellular organelle responsible for biological CO 2 assimilation, is ...
IEEE

A High-Performance Deep-Learning-Based Ground Penetrating Radar Classification Approach With Special Focus on Multi-Class Robustness

Abstract: Urbanization is increasing the presence of various utilities in the ground, while at the same time underground cavities and sinkholes pose a major threat to the civilization and structural ...
Visual Studio Magazine

Tsetlin Machine Binary Classification Using C#

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
IEEE

Bi-SSFormer: An Ultralightweight Binary Spectral–Spatial Transformer for Hyperspectral Image Classification

Abstract: With the advancement of deep learning techniques, deep neural networks have progressively supplanted traditional machine learning methods for hyperspectral image (HSI) classification, ...
SciELO

Classification of non-small cell lung cancer by histologic subtype using deep learning in public and private data sets of computed tomography images

Objective: To develop a deep learning system to classify non-small cell lung cancer (NSCLC) by histologic subtype—adenocarcinoma or squamous cell carcinoma (SCC)—from computed tomography (CT) images ...