Facial emotion recognition music player: Enhancing music experience through computer vision and machine learning

AIP conference proceedings, Journal Year: 2024, Volume and Issue: 3072, P. 040017 - 040017

Published: Jan. 1, 2024

Face Emotion Detection Music Player is an innovative idea that combines computer vision and machine learning techniques to create a unique interactive music player. This Research Paper studies the uses of Convolutional Neural Networks (CNN) detect analyze facial emotions in real-time dynamically playlists based on detected emotions. The player designed record expressions using webcam or other suitable camera. To reliably identify including happiness, sorrow, rage, surprise, more, CNN model trained sizable collection face images. demonstrated astounding 74.46% accuracy identifying when combined with software running PC device. analyses photos determine user's emotional state as they interact real-time, captured by Based emotions, automatically selects plays songs from predefined matches state. For example, if user looks happy, can play happy energetic songs, while angry, it more calming soothing music. offers personalized dynamic listening experience selection constantly updated according research paper illustrates how may be used produce programs instantly adjust moods preferences their users. It has research, entertainment, mental health, among others.

Language: Английский

---

Virtual Reality Technology and Artificial Intelligence for Television and Film Animation

Journal of Advanced Research in Applied Sciences and Engineering Technology, Journal Year: 2024, Volume and Issue: 43(1), P. 263 - 273

Published: April 9, 2024

Artificial intelligence technology has transformed television content and production methods resulted in the development of a new generation artificially intelligent Television. Popularising artificial improves programme content, categories, cost, efficiency. Virtual reality (VR) been widely used scientific study everyday life; thus, its use film animation (FTA) teaching researched to promote FTA learning. First, learning design uses dynamic environment modelling, real-time 3D graphic production, stereoscopic displays, sensors, other VR technologies. These four issues were due present primary method. enhances FTA's basic training teaching, course increase professional skill teaching. The application effect compares analyses classroom satisfaction, comprehensive quality evaluation, core curriculum effect. group's thorough evaluation is significantly improved, students' satisfaction with atmosphere, style, facilities 85%, 78%, 97.34%, respectively. This group can incorporate process into modelling finish work well. Compared traditional instruction, pupils are happier harvest more. Thus, instruction student engagement, efficiency, knowledge abilities. After analysing mode effects, be

Language: Английский

---

The sentiment analysis and emotion detection of COVID-19 online education tweets using ML techniques

AIP conference proceedings, Journal Year: 2024, Volume and Issue: 3072, P. 020004 - 020004

Published: Jan. 1, 2024

The COVID-19 outbreak impacted drastically to education and most of educational institutions started preferring online for students. However, after the settlement pandemic there is uncertainty among people about whether they should prefer furthermore or start in offline mode make it more interactive, so this paper an analysis people's sentiments emotions through Tweets Education. This aims study reaction around world toward during COVID-19. conducted on basis responses students, teachers, parents, college professors, etc. We with labeling data into three namely positive, neutral, negative validation then we used Machine learning (ML) classifiers namely, Logistic regression, Decision tree, Random Forest, Multilayer Perceptron (MLP), Naïve Bayes, Support vector machine (SVM), K-nearest neighbors (KNN), XG-Boost. Then performed emotion detection by considering 5 happy, surprise, sad, fear, angry ML classifiers. After applying all these approaches, XG Boost classifier achieved highest accuracy 94% classifying tweets as negative, 96% surprised, fearful, angry.

Language: Английский

---

Pneumonia Classification Model using Deep Learning Algorithm

Published: May 5, 2023

The bacteria Streptococcus pneumoniae is the cause of pneumonia, a potentially fatal infectious disease that affects one or both lungs in humans. According to World Health Organization (WHO), pneumonia blame for every three fatalities India. Three classification categories are considered this paper: Healthy, Viral and Bacterial infection. Chest X-rays used diagnose must be evaluated by experienced radiotherapists medical sector. By combining different techniques, new hybrid Convolutional Neural Network (CNN) model suggested regard. To classify CXR images, first method makes use Fully-Connected (FC) layers. weights result highest level accuracy retained after has been trained over number epochs. In second classification, Machine Learning (ML) classifiers optimized extract features most representative images. proposed an ensemble third With 98.55 percent, outcomes demonstrate classifier, which combines Support Vector (SVM), other performs best. Finally, create Computer Automated Detection system radiologists can accurately detect pneumonia.

Language: Английский

---

Deep Learning Based Face Mask Detection Model For COVID-19 Prevention

Published: May 5, 2023

After the epidemic spread around globe, particularly in underdeveloped nations poor countries, World Health organization (WHO) deemed Novel Corona Virus (Covid-19) to be a dangerous virus order protect social security. People should limit their contact with other people, wash hands often, and wear masks since there are few antiviral treatments healthcare resources. As part of safety procedures, worn. At airports, offices, shopping centres, hospitals, public locations COVID-enforcement police present every nation. Under these circumstances, doctors health professionals unable influence patients' situations. Identification wearer's face mask is more effective method preventing infection than human monitoring. Python, deep learning, computer vision have all been integrated into this work effectively Keras/OpenCV detector. Examining outcomes system comparison several detection approaches.

Language: Английский

---

Classification Of Chest X-ray Images Of Covid-19 By Deep Learning Based CNN Model and Attention Mechanism

Published: May 5, 2023

Covid-19 is a highly infectious viral disease that has been found in broad range of animal species, including humans. This fatal virus threatens not just people's lives, but also their health and the country's economy. Although serious widespread disease, there presently no vaccine available to protect against it. Clinical research conducted on people who contracted COVID-19 respiratory system was most common location infection after exposure virus. When it comes diagnosis lung-related illnesses, imaging modalities such as chest CT x-ray (also known radiography) are superior. The cost scan more than thorough x-ray, latter much cheaper. machine learning, deep learning provides impressive results. It valuable insight may be used investigation large number images, which have substantial impact Covid19 screening procedure. Specifically, this will apply attention method resnet50 features. Six thousand four hundred thirty-two samples were generated once feature process finished using Xgboost for validation Kaggle repository. These split between 965 examples 5467 training examples. proposed model (resnet-attention-xgboost) obtained 98.34 percent, while supplemented dataset reached 99 when came identifying X-ray pictures. comparison earlier models. study purely concerned with prospective categorization methodologies patients infected covid-19.

Language: Английский

---

Using Machine Learning to Improve Healthcare: A Disease Prediction and Management System

Published: May 5, 2023

For better patient diagnosis and treatment, medical facilities need to be advanced. With the assistance of machine learning, we can large sophisticated datasets for analyzing them getting clinical insights. Then, doctors use this continue offering care. Therefore, learning boost happiness when it is used in healthcare. We try incorporate skills into a single healthcare system work. By using precise predictive algorithms replace with disease prediction, made smarter. In some situations, cannot detected its earliest stages. prediction applied successfully. Prediction diseases epidemic outbreaks might result an early prevention disease's emergence, as said by wise, "Prevention than cure." The major focus paper development enhanced system, or more accurately, urgent provision that would symptoms. Because there so much metadata available different formats, user becomes perplexed. recommender system's purpose adapt particular user-related demands health department.

Language: Английский

---

A Comprehensive study on the Detection of Pneumonia using Machine Learning and Deep Learning Approaches

Published: May 5, 2023

Pneumonia is an inflammation of the lungs caused by a bacterial or viral infection. The air bags fill with pus when infected bacteria viruses. It can affect both single. also be fungi parasites. This illness that threatens lives millions people worldwide.. At present, main challenge to detect disease in itsearliest stages. typically diagnosed examining chest X-ray taken trained physician radiologist. In this review paper, database X-ray, CT-Scan images from patients was used automatically pneumonia.The patient's breathing becomes progressively unpleasant and difficult as result pneumonia. Machine learning-based diagnosis techniques aid early efficient detection disease. Medical imaging research utilizing computer vision-related automatic algorithm.

Language: Английский

---

A Survey on the role of ML and AI in fighting Covid-19

Published: May 5, 2023

Believed to have been originated Chinese province Wuhan in December 2019, the coronavirus has said cause 95 million cases with overall death rate of 2% (as per Jan 2022). As today China is still facing threat virus emerging again. This fast-spreading pandemic poses a challenge at world level and proposes serious danger people's health as well economy. With time regions this undergone several mutations resulting rise various other viruses, OMICRON being latest. The most common widely faced disease was case asymptomatic patients, ones who showed no symptoms yet were carriers deadly virus. In recent times, many researchers started exploring methods for predicting using medical parameters. Few commonly used technologies same are Machine Learning Artificial Intelligence. present paper aims exhibit role these presence. Various models by prediction corona compiled presented paper.

Language: Английский

---

A Hybrid Deep Neural approach for multi-class Classification of novel Corona Virus (COVID-19) using X-ray images

Published: May 5, 2023

People all around the world are facing challenges to survive due Corona Virus (Covid-19). Pneumonia is often caused by COVID-19. Biomedical field has witnessed success of Artificial Intelligence (AI) models for automatic diseases analyses and detection. Deep Learning (DL), a sub-field AI, used in this work classify COVID-19 from Normal patients. Three architectures i.e., Novel Convolutional Neural Network (N-CNN), Network- Long Short-Term Memory (CNN-LSTM) Network-Random Forest (CNN-RF) proposed classification covid19 images pneumonia normal cases. We have X-ray image dataset which 1212 training consists 404 each class 300 validation 100 class. Five pre-trained (VGG-19, VGG16, ResNet50, Inception v3 Inceptio$\mathrm{n}_{-}$ResNetv2) compare performance with models. Among these three models, CNN-RF model outperformed achieved an accuracy 94.66% whereas N-CNN CNN-LSTM got 89.67% 90.33% respectively.

Language: Английский

---