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Exploiting Concepts of Instance Segmentation to Boost Detection in Challenging Environments.

Sensors (Basel, Switzerland)
In recent years, due to the advancements in machine learning, object detection has become a mainstream task in the computer vision domain. The first phase of object detection is to find the regions where objects can exist. With the improvements in de...

Using Convolutional Neural Networks for the Assessment Research of Mental Health.

Computational intelligence and neuroscience
Existing mental health assessment methods mainly rely on experts' experience, which has subjective bias, so convolutional neural networks are applied to mental health assessment to achieve the fusion of face, voice, and gait. Among them, the OpenPose...

Robust Facial Landmark Detection by Multiorder Multiconstraint Deep Networks.

IEEE transactions on neural networks and learning systems
Recently, heatmap regression has been widely explored in facial landmark detection and obtained remarkable performance. However, most of the existing heatmap regression-based facial landmark detection methods neglect to explore the high-order feature...

Objective and automatic grading system of facial signs from selfie pictures of South African women: Characterization of changes with age and sun-exposures.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
OBJECTIVE: To evaluate the capacity of the automatic detection system to accurately grade, from smartphones' selfie pictures, the severity of fifteen facial signs in South African women and their changes related to age and sun-exposure habits.

Evaluation of Different Bearing Fault Classifiers in Utilizing CNN Feature Extraction Ability.

Sensors (Basel, Switzerland)
In aerospace, marine, and other heavy industries, bearing fault diagnosis has been an essential part of improving machine life, reducing economic losses, and avoiding safety problems caused by machine bearing failures. Most existing bearing fault dia...

TOD-CNN: An effective convolutional neural network for tiny object detection in sperm videos.

Computers in biology and medicine
The detection of tiny objects in microscopic videos is a problematic point, especially in large-scale experiments. For tiny objects (such as sperms) in microscopic videos, current detection methods face challenges in fuzzy, irregular, and precise pos...

MC-GCN: A Multi-Scale Contrastive Graph Convolutional Network for Unconstrained Face Recognition With Image Sets.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, a Multi-scale Contrastive Graph Convolutional Network (MC-GCN) method is proposed for unconstrained face recognition with image sets, which takes a set of media (orderless images and videos) as a face subject instead of single media (a...

Deep learning for biomechanical modeling of facial tissue deformation in orthognathic surgical planning.

International journal of computer assisted radiology and surgery
PURPOSE: Orthognathic surgery requires an accurate surgical plan of how bony segments are moved and how the face passively responds to the bony movement. Currently, finite element method (FEM) is the standard for predicting facial deformation. Deep l...

Automated Facial Expression Recognition Framework Using Deep Learning.

Journal of healthcare engineering
Facial expression is one of the most significant elements which can tell us about the mental state of any person. A human can convey approximately 55% of information nonverbally and the remaining almost 45% through verbal communication. Automatic fac...

Motion Fatigue State Detection Based on Neural Networks.

Computational intelligence and neuroscience
Aiming at the problem of fatigue state detection at the back of sports, a cascade deep learning detection system structure is designed, and a convolutional neural network fatigue state detection model based on multiscale pooling is proposed. Firstly,...