|
|
|
|
|
James Coe and Mustafa Atay
|
|
|
|
|
|
|
|
|
|
|
Amir Dirin,Nicolas Delbiaggio,Janne Kauttonen
Pág. pp. 121 - 133
Abstract? Computer visions and their applications have become important in contemporary life. Hence, researches on facial and object recognition have become increasingly important both from academicians and practitioners. Smart gadgets such as smartphone...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dongfei Xue, Xiaonian Wang, Jin Zhu, Darryl N. Davis, Bing Wang, Wenbing Zhao, Yonghong Peng and Yongqiang Cheng
Some machine learning algorithms have shown a better overall recognition rate for facial recognition than humans, provided that the models are trained with massive image databases of human faces. However, it is still a challenge to use existing algorithm...
ver más
|
|
|
|
|
|
|
|
|
|
|
Wenjun Bai, Changqin Quan and Zhiwei Luo
Featured Application: The proposed Uncertainty Flow framework may benefit the facial analysis with its promised elevation in discriminability in multi-label affective classification tasks. Moreover, this framework also allows the efficient model training...
ver más
|
|
|
|
|
|
|
|
|
|
|
Andrea Generosi, José Yuri Villafan, Luca Giraldi, Silvia Ceccacci and Maura Mengoni
Nowadays, web designers are forced to have an even deeper perception of how users approach their products in terms of user experience and usability. Remote Usability Testing (RUT) is the most appropriate tool to assess the usability of web platforms by m...
ver más
|
|
|
|
|
|
|
|
|
|
|
E.E. Istratova,D.N. Dostovalov,E.A. Bukhamer
Pág. 41 - 45
Personal identification systems are widely used in everyday life. There are many methods for extracting faces in the original image, the most perspective of which is the usage of algorithms based on neural networks. The aim of the study was to design and...
ver más
|
|
|
|
|
|
|
|
|
|
|
Dapeng Lang, Deyun Chen, Jinjie Huang and Sizhao Li
Small perturbations can make deep models fail. Since deep models are widely used in face recognition systems (FRS) such as surveillance and access control, adversarial examples may introduce more subtle threats to face recognition systems. In this paper,...
ver más
|
|
|
|
|
|
|
|
|
|
|
Aluizio Rocha Neto, Thiago P. Silva, Thais Batista, Flávia C. Delicato, Paulo F. Pires and Frederico Lopes
In smart city scenarios, the huge proliferation of monitoring cameras scattered in public spaces has posed many challenges to network and processing infrastructure. A few dozen cameras are enough to saturate the city?s backbone. In addition, most smart c...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexey Semenkov, Dmitry Bragin, Yakov Usoltsev, Anton Konev and Evgeny Kostuchenko
Modern facial recognition algorithms make it possible to identify system users by their appearance with a high level of accuracy. In such cases, an image of the user?s face is converted to parameters that later are used in a recognition process. On the o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kudakwashe Zvarevashe and Oludayo Olugbara
Automatic recognition of emotion is important for facilitating seamless interactivity between a human being and intelligent robot towards the full realization of a smart society. The methods of signal processing and machine learning are widely applied to...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fauziah Fauziah
Pág. 53 - 61
One area of science that can apply facial recognition applications is artificial intelligence. The algorithms used in facial recognition are quite numerous and varied, but they all have the same three basic stages, face detection, facial extraction and f...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shiplu Das, Sanjoy Pratihar, Buddhadeb Pradhan, Rutvij H. Jhaveri and Francesco Benedetto
The main purpose of a detection system is to ascertain the state of an individual?s eyes, whether they are open and alert or closed, and then alert them to their level of fatigue. As a result of this, they will refrain from approaching an accident site. ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
ver más
|
|
|
|
|
|
|
|
|
|
|
Thomas Kopalidis, Vassilios Solachidis, Nicholas Vretos and Petros Daras
Recent technological developments have enabled computers to identify and categorize facial expressions to determine a person?s emotional state in an image or a video. This process, called ?Facial Expression Recognition (FER)?, has become one of the most ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yue Pang, Wenbo Yu, Chuanzhong Xuan, Yongan Zhang and Pei Wu
The mutton sheep breeding industry has transformed significantly in recent years, from traditional grassland free-range farming to a more intelligent approach. As a result, automated sheep face recognition systems have become vital to modern breeding pra...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mei Bie, Huan Xu, Quanle Liu, Yan Gao, Kai Song and Xiangjiu Che
Facial expression recognition (FER) is an important field in computer vision with many practical applications. However, one of the challenges in FER is dealing with small sample data, where the number of samples available for training machine learning al...
ver más
|
|
|
|
|
|
|
|
|
|
|
Munir Ahmad, Sagheer Abbas, Areej Fatima, Ghassan F. Issa, Taher M. Ghazal and Muhammad Adnan Khan
The importance of accurate livestock identification for the success of modern livestock industries cannot be overstated as it is essential for a variety of purposes, including the traceability of animals for food safety, disease control, the prevention o...
ver más
|
|
|
|
|
|
|
|
|
|
|
Tony Gwyn and Kaushik Roy
Image recognition technology systems have existed in the realm of computer security since nearly the inception of electronics, and have seen vast improvements in recent years. Currently implemented facial detection systems regularly achieve accuracy rate...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zewei Wang, Yongjun Zhang, Chengchang Pan and Zhongwei Cui
Principal Component Analysis Network (PCANet) is a lightweight deep learning network, which is fast and effective in face recognition. However, the accuracy of faces with occlusion does not meet the optimal requirement for two reasons: 1. PCANet needs to...
ver más
|
|
|
|
|
|
|
|
|
|
|
E.E. Istratova,D.A. Pustovskih
Pág. 66 - 74
To increase the reliability and efficiency of work in most information systems, biometric identification technologies are used, where the image of a person's face is used as an object of study. The aim of the study was to develop a biometric data validat...
ver más
|
|
|
|
|
|