Evolving an emotion recognition module for an intelligent agent using genetic programming and a genetic algorithm

Yusuf, Rahadian; Sharma, Dipak Gaire; Tanev, Ivan; Shimohara, Katsunori

doi:10.1007/s10015-016-0263-z

Cited by 13 publications

(5 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Machine learning [18,21,22,[24][25][26][27][28][29][30][33][34][35][36][37][40][41][42][43]45,48,49] Deep learning [22,25,26,30,38,39,41,[44][45][46][47] Zangerle et al [50] make a critical note that many studies sensing emotions take place in laboratory settings. This is also reflected in this work, as can be seen in Table 3.…”

Section: Methods Referencesmentioning

confidence: 99%

See 1 more Smart Citation

Utilising Emotion Monitoring for Developing Music Interventions for People with Dementia: A State-of-the-Art Review

Vuijk

Brinke

Sharma

2023

Sensors

View full text Add to dashboard Cite

The demand for smart solutions to support people with dementia (PwD) is increasing. These solutions are expected to assist PwD with their emotional, physical, and social well-being. At the moment, state-of-the-art works allow for the monitoring of physical well-being; however, not much attention is delineated for monitoring the emotional and social well-being of PwD. Research on emotion monitoring can be combined with research on the effects of music on PwD given its promising effects. More specifically, knowledge of the emotional state allows for music intervention to alleviate negative emotions by eliciting positive emotions in PwD. In this direction, the paper conducts a state-of-the-art review on two aspects: (i) the effect of music on PwD and (ii) both wearable and non-wearable sensing systems for emotional state monitoring. After outlining the application of musical interventions for PwD, including emotion monitoring sensors and algorithms, multiple challenges are identified. The main findings include a need for rigorous research approaches for the development of adaptable solutions that can tackle dynamic changes caused by the diminishing cognitive abilities of PwD with a focus on privacy and adoption aspects. By addressing these requirements, advancements can be made in harnessing music and emotion monitoring for PwD, thereby facilitating the creation of more resilient and scalable solutions to aid caregivers and PwD.

show abstract

Section: Methods Referencesmentioning

confidence: 99%

“…Deep learning: CNN [39], genetic programming [45], MLP [41], probablistic neural networks [41], and RNN with LSTM [38].…”

mentioning

confidence: 99%

Utilising Emotion Monitoring for Developing Music Interventions for People with Dementia: A State-of-the-Art Review

Vuijk

Brinke

Sharma

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Yusuf uses genetic programming and genetic algorithms to improve the emotional recognition module of the intelligent subject. To realize the exploration of cultural exchange paths in an intelligent environment, the improvement of intelligent algorithms is essential [6].…”

Section: Introductionmentioning

confidence: 99%

Exploration of the Path of Sino-Japanese Cultural Exchange under the Development of Intelligent Internet Integration

2021

IJAID

View full text Add to dashboard Cite

With the advancement of Internet technology, the Internet is no longer just a carrier for humans to receive and transmit information, but also to achieve a close connection between people and things, and things and things. Based on the current situation of Sino-Japanese cultural exchanges, this article attempts to explore new paths for cultural exchanges in a smart environment. This article uses smart sensor technology to build an intelligent cultural exchange platform model, which provides an online cultural exchange platform for people who love Chinese and Japanese cultures. Users can upload their cultural insights to the platform through the Internet, and the smart sensors in the platform will analyze the content in combination with smart algorithms, filter out the content containing sensitive words, and leave only valuable cultural exchange information. In addition, smart sensors can also analyze all the data in the platform and make intelligent decisions to better meet the demands and expectations of target users in the process of cultural exchanges. According to the platform data, 34.77% of users have posted cultural-related knowledge issues on the platform for help. In contrast, although the content of cultural events only accounts for 7.38%, they can promote the connection of online and offline cultural exchange activities, and better promote various offline cultural activities through online platforms.

show abstract

“…Facial expression recognition (FER) has attracted much attention recently, and owing to its wide applicability, FER plays an important role in recognising human emotions [1][2][3][4]. In general, there are seven expressions, namely, anger, disgust, fear, happiness, sadness, surprise, and neutral [5,6].…”

Section: Introductionmentioning

confidence: 99%

Discriminative feature learning‐based pixel difference representation for facial expression recognition

Sun

Wang

et al. 2017

IET Computer Vision

View full text Add to dashboard Cite

Recently, researchers have proposed different feature descriptors to achieve robust performance for facial expression recognition (FER). However, finding a discriminative feature descriptor remains one of the critical tasks. In this paper, we propose a discriminative feature learning scheme to improve the representation power of expressions. First, we obtain a discriminative feature matrix (DFM) based pixel difference representation. Subsequently, all DFMs corresponding to the training samples are used to construct a discriminative feature dictionary (DFD). Next, DFD is projected on a vertical two-dimensional linear discriminant analysis in direction (V-2DLDA) space to compute between and within-class scatter because V-2DLDA works well with the DFD in matrix representation and achieves good efficiency. Finally, nearest neighbor (NN) classifier is used to determine the labels of the query samples. DFD represents the local feature changes that are robust to the expression, illumination et al. Besides, we exploit V-2DLDA to find an optimal projection matrix since it not only protects the discriminative features but reduces the dimensions. The proposed method achieves satisfying recognition results, reaching accuracy rates as high as 91.87% on CK+ database, 82.24% on KDEF database, and 78.94% on CMU Multi-PIE database in the LOSO scenario, which perform better than other comparison methods.

show abstract

Evolving an emotion recognition module for an intelligent agent using genetic programming and a genetic algorithm

Cited by 13 publications

References 6 publications

Utilising Emotion Monitoring for Developing Music Interventions for People with Dementia: A State-of-the-Art Review

Utilising Emotion Monitoring for Developing Music Interventions for People with Dementia: A State-of-the-Art Review

Exploration of the Path of Sino-Japanese Cultural Exchange under the Development of Intelligent Internet Integration

Discriminative feature learning‐based pixel difference representation for facial expression recognition

Contact Info

Product

Resources

About