Results 141 to 150 of about 1,466 (208)

MTCNN++: A CNN-based face detection algorithm inspired by MTCNN

The Visual Computer, 2023
Soumya Suvra Khan, Diganta Sengupta, Anupam Ghosh, Atal Chaudhuri   +3 more
openaire   +2 more sources

Tracking Student Attendance in Virtual Classes Based on MTCNN and FaceNet

Lecture Notes in Computer Science, 2022
Trong-Nghia Pham, Nam-Phong Nguyen, Thanh Le   +2 more
exaly   +2 more sources

Face image authentication scheme based on MTCNN and SLT

Multimedia Tools and Applications
Rasha Thabit, Mohanad A. Al-Askari, Dunya Zeki Mohammed, Elham Abdulwahab Anaam, Zainab H. Mahmood, Dina Jamal Jabbar, Zahraa Aqeel Salih   +6 more
openaire   +2 more sources

Comparative Study of MTCNN and YuNet for Deepfake Detection

Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies
: In recent years, deepfakes have become a prominent digital threat, raising concerns about the potential harm they can inflict on personal privacy and the fabric of society as trust in visual evidence becomes increasingly compromised.
M. Adithya, C. Tanush, N. Kathyaini, D. Reddy, G. Latha   +4 more
openaire   +2 more sources

Face Mask Recognition Based on MTCNN and MobileNet

2021 3rd International Academic Exchange Conference on Science and Technology Innovation (IAECST), 2021
The COVID-19 can be transmitted by air droplets, aerosols, and other carriers, the spread of the virus can be effectively prevented by wearing masks in public. Therefore, it is meaningful to identify whether a mask is worn in particular places. In this paper, a method based on multi-task convolutional neural networks (MTCNN) and MobileNet algorithms is
Jianzhao Cao, Renning Pang, Ruwei Ma, Yuanwei Qi   +3 more
openaire   +2 more sources

MTCNN Based on Gaussian Mixture Image Pyramid

2020 the 3rd International Conference on Control and Computer Vision, 2020
As the first two steps of face recognition system, face detection and key point location are of great significance to the accuracy of face recognition system. The Multi-task Cascaded Convolutional Network(MTCNN) uses a single network model for the first time to complete the task of face detection and key point location.
Ting Wang, Yao Ma, Yuefeng Lu
openaire   +1 more source

Research on the Improvement of MTCNN ALGORITHM: Face Recognition with Mask

2021 2nd International Conference on Artificial Intelligence and Information Systems, 2021
During the 2019-nCoV epidemic, in order to effectively prevent the spread of the virus, people generally wore masks when entering public places, rendering traditional facial recognition technology ineffective. This paper constructs a dataset of face images with masks, and proposes a face recognition algorithm for masks based on deep learning.
Jian Xiao, Jia Wang, Shaozhong Cao, Yang Li   +3 more
openaire   +1 more source

Research on Face Detection Technology Based on MTCNN

2020 International Conference on Computer Network, Electronic and Automation (ICCNEA), 2020
Face detection is an important research direction in the field of target detection. For the input image, the position of the face is returned. In order to complete the task of face detection using deep learning, data input, feature extraction and face feature detection are three steps, among which feature extraction is the most important part.
Ning Zhang, Junmin Luo, Wuqi Gao
openaire   +1 more source

BYOL Yaklasimini Kullanarak MTCNN ile Yakalanan Yüzlerde Deepfake Tespiti Deepfake Detection on Faces Captured with MTCNN, by Using the BYOL Approach

2024 Innovations in Intelligent Systems and Applications Conference (ASYU)
Huseyin Polat
exaly   +2 more sources

Comparing MTCNN and Viola-Jones Algorithm in Face Recognition

2024 19th Iranian Conference on Intelligent Systems (ICIS)
Anahita Bahmeie, Maryam Shakiba
exaly   +2 more sources