Search Results - (( emotion detection model algorithm ) OR ( data classification using algorithmic ))
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
Published 2023“…Despite extensive research employing machine learning algorithms like convolutional neural networks (CNN), challenges remain concerning input data processing, emotion classification scope, data size, optimal CNN configurations, and performance evaluation. …”
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Deep learning based emotion recognition for image and video signals: matlab implementation
Published 2021“…Different pre-processing steps have been carried over data samples, followed by the popular and efficient Viola-Jones algorithm for face detection. …”
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Eye fixation versus pupil diameter as eye- tracking features for virtual reality emotion classification
Published 2022“…Three separate experiments were conducted using Support Vector Machines (SVMs) as the classification algorithm for the two chosen eye features. …”
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Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection
Published 2023“…So besides writer sentiments, writer emotion is also a valuable data. Emotion detection can be done using text, facial expressions, verbal communications and brain waves; however, the focus of this review is on text-based sentiment analysis and emotion detection. …”
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…Five functional layers are the components of the model architecture. The above are the major components of a vision system: Data Acquisition, Multimodal Preprocessing, Cross-Media Feature Extraction, Emotional Value Detection and Moderation, and Interpretability and Visualization. …”
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Detecting emotions and depression through voice
Published 2021“…A deep learning algorithm can detect emotion, including depression, using a voice signal. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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Emotion Modelling Using Neural Network
Published 2005“…This study attempts to model emotion using neural network technique. Six primary emotions considered in this study are anger, disgust, fear, happiness, sadness and surprise. …”
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The design for antrophomorphic sociable agent interaction through emotion detection
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…Some of the dengue data are used to test the dengue classification system to produce the classification accuracy. …”
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Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Implementing this process uses classification algorithms such asNaïve Bayes, Support Vector Machine,and Random Forest. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. …”
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Affective computation on EEG correlates of emotion from musical and vocal stimuli
Published 2009“…Affective interface that acquires and detects the emotion of the user can potentially enhance the humancomputer interface experience. …”
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Proceeding Paper -
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Firstly, it aims to use both linear and nonlinear features of EEG signals to identify emotional influences on gender behavior. Secondly, it aims to develop an automatic gender recognition model by employing optimization algorithms to identify the most effective channels for gender identification from emotional-based EEG signals. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Expectation maximization (EM) is one of the representatives clustering algorithms which have broadly applied in solving classification problems by improving the density of data using the probability density function. …”
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