A comprehensive survey on encryption techniques for digital images
With the widespread adoption of smart devices and high-speed networks, investigators are focusing on securing digital image applications, such as those on social media, in healthcare, education, business and defence, from unauthorised use. The aim ...
Benchmarking deep networks for facial emotion recognition in the wild
Emotion recognition from face images is a challenging task that gained interest in recent years for its applications to business intelligence and social robotics. Researchers in computer vision and affective computing focused on optimizing the ...
A novel image dataset for source camera identification and image based recognition systems
Multimodal emotion recognition has attracted a great deal of attention in recent years, with new interesting applications now being considered. One promising application is in the digital image forensics fields where, for example, it gives the ...
Joint modelling of audio-visual cues using attention mechanisms for emotion recognition
Emotions play a crucial role in human-human communications with complex socio-psychological nature. In order to enhance emotion communication in human-computer interaction, this paper studies emotion recognition from audio and visual signals in ...
A method for simplifying the spoken emotion recognition system using a shallow neural network and temporal feature stacking & pooling (TFSP)
This study presents a new speech emotion recognition (SER) technique using temporal feature stacking and pooling (TFSP). First, Mel-frequency cepstral coefficients, Mel-spectrogram, and emotional silence factor (ESF) are extracted from segmented ...
Enhancing the accuracy of a human emotion recognition method using spatial temporal graph convolutional networks
Artificial intelligence technology has been widely used in human emotion recognition applications. Unlike traditional facial, semantic and brain wave technology, spatio-temporal graph convolution network technology has been shown to be useful for ...
The limitations for expression recognition in computer vision introduced by facial masks
Facial Expression recognition is a computer vision problem that took relevant benefit from the research in deep learning. Recent deep neural networks achieved superior results, demonstrating the feasibility of recognizing the expression of a user ...
Emotion recognition by web-shaped model
Emotions recognition is widely applied for many tasks in different fields, from human-computer and human-robot interaction to learning platforms. Also, it can be used as an intrinsic approach for face recognition tasks, in which an expression-...
CMHE-AN: Code mixed hybrid embedding based attention network for aggression identification in hindi english code-mixed text
The widespread growth in social media platforms provides a plethora of opportunities to enhance interaction and bring awareness about recent activities happening across the countries. Many people use social media to share their thoughts and ...
Facial emotion recognition based real-time learner engagement detection system in online learning context using deep learning models
The dramatic impact of the COVID-19 pandemic has resulted in the closure of physical classrooms and teaching methods being shifted to the online medium.To make the online learning environment more interactive, just like traditional offline ...
Facial expression analysis in a wild sporting environment
- Oliverio J. Santana,
- David Freire-Obregón,
- Daniel Hernández-Sosa,
- Javier Lorenzo-Navarro,
- Elena Sánchez-Nielsen,
- Modesto Castrillón-Santana
The scientific community and mass media have already reported the use of nonverbal behavior analysis in sports for athletes’ performance. Their conclusions stated that certain emotional expressions are linked to athlete’s performance, or even that ...
Interpersonal relation recognition: a survey
People spend a considerable amount of their time in social activities, where person-to-person relations are of main relevance. Recently, there has been an increasing research interest in automatically analyzing interpersonal relations, for the ...
A statistical feature extraction for deep speech emotion recognition in a bilingual scenario
Previously and currently, most of literature works on Speech Emotion Recognition (SER) have been orientated towards a monolingual approach. The current study extends monolingual SER to a bilingual setting. However, in order to construct a ...
A hybrid deep feature selection framework for emotion recognition from human speeches
Speech Emotion Recognition (SER) is an active area of signal processing research that aims at identifying emotional states from audio speech signals. Applications of SER range from psychological diagnosis to human-computer interaction and as such, ...
Improved convolutional neural network-based approach using hand-crafted features for facial expression recognition
Facial expression recognition is still one of the most attractive and challenging problems. This study designed a facial expression recognition approach based on the feature fusion strategy. In this proposed approach, two types of features are ...
Variation of deep features analysis for facial expression recognition system
In this paper, a unique facial expression recognition system has been proposed. The objective of this paper is to identify the type of human facial expression and to improve the performance by incorporating different variant patterns present in ...
A computer vision-based perceived attention monitoring technique for smart teaching
This paper aims to improve the lecture delivery mechanism in real-time in a classroom and remote sessions over web-based applications. In the traditional system, a lecturer observes their students’ attention levels from his/her experience. To date,...
Compound facial expressions image generation for complex emotions
This work presents the methodology to synthesize the complex facial expressions images from the learned representation without specifying emotion labels as input. The proposed methodology consists of three main modules: the basic emotion ...
Micro-information-level AR instruction: a new visual representation supporting manual classification of similar assembly parts
In AR operation guidance training, for assembly parts with similar geometric shapes, there are still two problems in the visual representation of AR instructions: (1) AR instructions cannot accurately represent the micro-geometric differences ...
ExpertosLF: dynamic late fusion of CBIR systems using online learning with relevance feedback
One of the main challenges in CBIR systems is to choose discriminative and compact features, among dozens, to represent the images under comparison. Over the years, a great effort has been made to combine multiple features, mainly using early, ...
Interactively transforming chinese ink paintings into realistic images using a border enhance generative adversarial network
Traditional Chinese painting has a long history. When we appreciate such paintings today, although we can obtain an overview of the landscape and environment of that time, it can be difficult to feel like we are interacting with the paintings. ...
A deep learning-based distracted driving detection solution implemented on embedded system
Distracted driving is one of the leading causes of most road accidents. Rectification of distracted driving activity is a big challenge for an intelligent transport system (ITS). The use of an in-vehicle deep learning-based driver assistance ...
Application in multimedia: from camera to VR
This work describes a framework that allows children and domestic users to create architectural structures like mazes, houses etc., and navigate them in virtual reality (VR). The user can draw a 2D map of a maze etc. using a simple paper, pen and ...
A new robust and fragile scheme based on chaotic maps and dwt for medical image security
Medical image security includes copyright protection, authentication, data integrity and confidentiality simultaneously. In this article, a new robust and fragile medical image security scheme has been introduced. The Beddington, Free and Lawton (...
Development iterations based on web augmentation and context tasks
The use of prototypes in requirements engineering has widely known benefits since they actively involve the stakeholders in the development process. Web Augmentation techniques make it possible to build prototypes relying on existing web ...
Augmented reality with algorithm animation and their effect on students’ emotions
Algorithm animations are a resource that assists in learning algorithms by visually displaying the behavior of an algorithm at a higher level of abstraction than source code. On the other hand, augmented reality is a technology that allows ...
Humanoid robot runs maze mode using depth-first traversal algorithm
This paper focuses on the humanoid robot walking in the maze. In this research, we proposed the depth-first traversal algorithm for the maze searching with the single-view model and sonar obstacle avoidance theory then follow the “turn right first”...
A new method proposed to Melanoma-skin cancer lesion detection and segmentation based on hybrid convolutional neural network
The number of deaths due to melanoma skin cancer has rapidly increased in recent years. The timely diagnosis of the lesions of melanoma skin cancer can potentially increase the survival rate of such a chronic disease. However, the detection of ...