Facial Emotion Recognition using Convolutional Neural Networks
Facial expression recognition is a topic of great interest in most fields from artificial intelligence and gaming to marketing and healthcare. The goal of this paper is to classify images of human faces into one of seven basic emotions. A number of different models were experimented with, including decision trees and neural networks before arriving at a final Convolutional Neural Network (CNN) model. CNNs work better for image recognition tasks since they are able to capture spacial features of the inputs due to their large number of filters. The proposed model consists of six convolutional layers, two max pooling layers and two fully connected layers. Upon tuning of the various hyperparameters, this model achieved a final accuracy of 0.60.
Code (0)
등록된 구현이 없습니다.
Tasks
Emotion RecognitionFacial Emotion RecognitionFacial Expression RecognitionFacial Expression Recognition (FER)MarketingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Leveraging Previous Facial Action Units Knowledge for Emotion Recognition on Faces
People naturally understand emotions, thus permitting a machine to do the same could open new paths for human-computer interaction. Facial expressions can be very useful for emotion recognition techniques, as these are t…
Emotion RecognitionI Know How You Feel: Emotion Recognition with Facial Landmarks
Classification of human emotions remains an important and challenging task for many computer vision algorithms, especially in the era of humanoid robots which coexist with humans in their everyday life. Currently propose…
ClassificationEmotion ClassificationEmotion RecognitionGeneral Classification+1Facial Emotion Recognition Using Transfer Learning in the Deep CNN
Human facial emotion recognition (FER) has attracted the attention of the research community for its promising applications. Mapping different facial expressions to the respective emotional states are the main task in FE…
Emotion RecognitionFacial Emotion RecognitionFacial Expression Recognition (FER)Transfer LearningGenerating Dataset For Large-scale 3D Facial Emotion Recognition
The tremendous development in deep learning has led facial expression recognition (FER) to receive much attention in the past few years. Although 3D FER has an inherent edge over its 2D counterpart, work on 2D images has…
Emotion RecognitionFacial Emotion RecognitionFacial Expression RecognitionFacial Expression Recognition (FER)A Robust Framework for Deep Learning Approaches to Facial Emotion Recognition and Evaluation
Facial emotion recognition is a vast and complex problem space within the domain of computer vision and thus requires a universally accepted baseline method with which to evaluate proposed models. While test datasets hav…
Emotion ClassificationEmotion RecognitionFacial Emotion Recognition