What is the FER2013 dataset?

The FER2013 dataset is a large-scale collection of over 35,000 labeled facial images used for training AI and machine learning models to recognize seven human emotions — anger, disgust, fear, happiness, sadness, surprise, and neutral.

How can this dataset be used in AI and machine learning projects?

The FER2013 dataset supports AI model development in areas such as emotion recognition, behavioral analytics, human-computer interaction, mental health assessment, and real-time surveillance systems.

Does GTS provide custom emotion recognition datasets?

Yes, GTS offers custom dataset collection and annotation services tailored to specific AI model requirements. Data can be collected across diverse demographics, including different age groups, ethnicities, and geographic regions.

How does GTS ensure dataset quality and compliance?

All datasets undergo manual annotation, multi-level quality checks, and secure data cleaning before delivery. GTS complies with global data protection laws, including GDPR and HIPAA, and operates under ISO 9001:2015 and ISO 27001:2013 standards.

In what formats can the dataset be delivered?

Datasets are available in JSON, CSV, or image file formats, with flexible delivery options for integration into AI and ML pipelines. Custom formatting can also be provided on request.

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