Understanding Human Face Shape via Inception-ResNet Neural Network Architecture

Shintami Chusnul Hidayati*, Jessica Tasyanita, Chastine Fatichah, Yeni Anistyasari

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In recent years, computer vision has advanced facial recognition applications across diverse domains, from security systems to augmented reality. Among the fundamental attributes of a face, shape plays a crucial role in distinguishing individuals and understanding their unique identities. This paper introduces an innovative approach to comprehending human face shape through the cutting-edge Inception-ResNet neural network architecture, which combines Inception with residual connections. The approach harnesses the rich discriminative features learned by this architecture to boost face shape recognition accuracy and robustness. Extensive experiments demonstrate the remarkable performance of the approach, surpassing traditional methods and prior deep learning models. Furthermore, to provide a holistic perspective on the individual contributions of various modules within our approach, we present a detailed ablation study.

Original languageEnglish
Title of host publication2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages631-636
Number of pages6
ISBN (Electronic)9798350309225
DOIs
Publication statusPublished - 2023
Event2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Lombok, Indonesia
Duration: 14 Nov 202315 Nov 2023

Publication series

Name2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023 - Proceedings

Conference

Conference2023 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2023
Country/TerritoryIndonesia
CityLombok
Period14/11/2315/11/23

Keywords

  • Inception-Resnet architecture
  • classification
  • face shape
  • facial recognition
  • innovation
  • neural network

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