Combining MTCNN and Enhanced FaceNet with Adaptive Feature Fusion for Robust Face Recognition
Face recognition systems typically face actual challenges like facial pose, illumination, occlusion, and ageing that significantly impact the recognition accuracy.
Saman Shojae Chaeikar
exaly +4 more sources
Automated Analysis of Spontaneous Facial Expression Variability in Neurocognitive Disorders During Naturalistic Conversation [PDF]
Abstract Background A comprehensive investigation of facial expression variability during naturalistic conversations was conducted across individuals with behavioral variant frontotemporal dementia (bvFTD), Alzheimer's disease (AD), mild cognitive impairment (MCI), and healthy controls (HC).
Pressman P +5 more
europepmc +2 more sources
Historical Blurry Video-Based Face Recognition [PDF]
Face recognition is a widely used computer vision, which plays an increasingly important role in user authentication systems, security systems, and consumer electronics.
Lujun Zhai +5 more
doaj +2 more sources
Improved MTCNN face detection algorithm fused with context features
The multi-task convolutional neural network (MTCNN) face detection algorithm has a low detection rate of small faces in classroom scenes. An improved MTCNN algorithm that integrates context features was thus proposed.
Meihua GU, Jing FENG, Na YANG
doaj +2 more sources
Real-world Attack on MTCNN Face Detection System [PDF]
Recent studies proved that deep learning approaches achieve remarkable results on face detection task. On the other hand, the advances gave rise to a new problem associated with the security of the deep convolutional neural network models unveiling potential risks of DCNNs based applications. Even minor input changes in the digital domain can result in
Mikhail Pautov
exaly +3 more sources
Multimodal deep learning with hyperspectral imaging for accurate origin classification of wolfberries [PDF]
Accurate classification of wolfberry geographical origin is essential for assessing its nutritional and medicinal properties. A multimodal convolutional neural network (MTCNN) with a cross-attention mechanism was proposed to effectively fuse spectral and
Bo Li +6 more
doaj +2 more sources
Simultaneous determination of pigments of spinach (Spinacia oleracea L.) leaf for quality inspection using hyperspectral imaging and multi-task deep learning regression approaches [PDF]
Rapid and accurate determination of pigment content is important for quality inspection of spinach leaves during storage. This study aimed to use hyperspectral imaging at two spectral ranges (visible/near-infrared, VNIR: 400–1000 nm; NIR: 900–1700 nm) to
Mengyu He +9 more
doaj +2 more sources
Computationally intelligent real-time security surveillance system in the education sector using deep learning. [PDF]
Real-time security surveillance and identity matching using face detection and recognition are central research areas within computer vision. The classical facial detection techniques include Haar-like, MTCNN, AdaBoost, and others.
Muhammad Mobeen Abid +5 more
doaj +2 more sources
Multi-face recognition and dynamic tracking based on reinforcement learning algorithm [PDF]
Aiming at the problem that the current low accuracy rate of face detection and target tracking, a reinforcement learning algorithm is proposed, which integrates face detection technology and target tracking technology organically, adopts the face ...
Li Yuxin, Xie Yinggang, Lu Xi
doaj +1 more source
Deep-Facial Feature-Based Person Re-identification for Authentication in Surveillance Applications [PDF]
Nowadays, a large network of cameras is predominantly used in public places which provide enormous video data. These data are monitored manually and may be utilized only when the need arises to ascertain the facts.
Borse Pranjal +3 more
doaj +1 more source

