A Multilevel Single Stage Network for Face Detection
نویسندگان
چکیده
منابع مشابه
Feature Agglomeration Networks for Single Stage Face Detection
Recent years have witnessed promising results of face detection using deep learning, especially for the family of region-based convolutional neural networks (R-CNN) methods and their variants. Despite making remarkable progresses, face detection in the wild remains an open research challenge especially when detecting faces at vastly different scales and characteristics. In this paper, we propos...
متن کاملResidual Features and Unified Prediction Network for Single Stage Detection
Recently, a lot of single stage detectors using multi-scale features have been actively proposed. They are much faster than two stage detectors that use region proposal networks (RPN) without much degradation in the detection performances. However, the feature maps in the lower layers close to the input which are responsible for detecting small objects in a single stage detector have a problem ...
متن کاملDetection of Brucella melitensis and Brucella abortus strains using a single-stage PCR method
Brucella melitensis and Brucella abortus are of the most important causes of brucellosis, an infectious disease which is transmitted either directly or indirectly including consuming unpasteurized dairy products. Both strains are considered endemic in Iran. Common diagnostic methods such as bacteriologic cultures are difficult and time consuming regarding the bacteria. The aim of this study w...
متن کاملNeural Network Based Approach for Face Detection cum Face Recognition
Automatic face detection is a complex problem in image processing. Many methods exist to solve this problem such as template matching, Fisher Linear Discriminate, Neural Networks, SVM, and MRC. Success has been achieved with each method to varying degrees and complexities. In proposed algorithm we used upright, frontal faces for single gray scale images with decent resolution and under good lig...
متن کاملSupervised Transformer Network for Efficient Face Detection
Large pose variations remain to be a challenge that confronts real-word face detection. We propose a new cascaded Convolutional Neural Network, dubbed the name Supervised Transformer Network, to address this challenge. The first stage is a multi-task Region Proposal Network (RPN), which simultaneously predicts candidate face regions along with associated facial landmarks. The candidate regions ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Wireless Communications and Mobile Computing
سال: 2021
ISSN: 1530-8677,1530-8669
DOI: 10.1155/2021/5582132