Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Archiving 4.0: Dataset Generation and Facial Recognition of DRC Political Figures Using Machine Learning

Type de record:

dataset
Créateur:
FerAntOla
Éditeur:
Spr
Hôte:

Visit

doi.org

Tasks

computer vision

Licenses

https://www.springernature.com/gp/researchers/text-and-data-mininghttps://www.springernature.com/gp/researchers/text-and-data-mining

Similaires

Adinkra Symbol Recognition using Classical Machine Learning and Deep LearningAnalysis of Ghanaian Political Sentiments using Deep Learning and Machine Learning ApproachesDates Fruit Disease Recognition using Machine LearningDevanagari Digit Recognition using Quantum Machine LearningSign Language Recognition System Using Machine LearningDesign and development of biometric voting system using fingerprint and facial recognition

Adinkra Symbol Recognition using Classical Machine Learning and Deep Learning

Artificial intelligence (AI) has emerged as a transformative influence, engendering paradigm shifts

Analysis of Ghanaian Political Sentiments using Deep Learning and Machine Learning Approaches

Over the past decade, with the growth of social media platforms such as Twitter, Instagram,

Dates Fruit Disease Recognition using Machine Learning

Many countries such as Saudi Arabia, Morocco and Tunisia are among the top exporters and consumers o

Devanagari Digit Recognition using Quantum Machine Learning

Handwritten digit recognition in regional scripts, such as Devanagari, is crucial for multilingual d

Sign Language Recognition System Using Machine Learning

Abstract: Voice and language is the main thing that people understand one with the other. We can und

Design and development of biometric voting system using fingerprint and facial recognition

The election process adopted in Nigeria is mostly paper based or manual. This manually handled proce