Identify if hands are raised in class
using AI
Below is a free classifier to identify if hands are raised in class. Just upload your image, and our AI will predict if hands are raised - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-hands-are-raised-in-class", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/if-hands-are-raised-in-class/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/if-hands-are-raised-in-class/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if hands are raised.
This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Hands Raised and Hands Not Raised.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if hands are raised).
Whether you're just curious or building if hands are raised in class detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify if hands are raised in class at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Classroom Engagement Analytics: This use case focuses on analyzing student engagement by identifying when students raise their hands during class. Educators can utilize this data to assess participation levels and adjust their teaching methods to enhance interactive learning experiences.
- Real-time Attendance Monitoring: The system can track hand-raising instances to confirm student presence and participation without traditional roll call methods. This can streamline attendance processes, allowing educators to focus on instruction rather than administrative tasks.
- Adaptive Learning Systems: By identifying raised hands, adaptive learning platforms can tailor content delivery based on student engagement. If students frequently signal for help, the system can adjust its difficulty level or offer additional resources to support their learning needs.
- Teacher Feedback Mechanism: Teachers can receive real-time feedback on student understanding and interest levels based on hand-raising frequency. This insight can guide teachers in modifying their pace or revisiting concepts that may require further clarification.
- Data-Driven Class Management: Schools can aggregate data from multiple classes to analyze trends in student participation across various subjects. This information can inform curriculum development and identify areas where students may need additional support or encouragement.
- Inclusive Education Monitoring: The hand-raising identifier can help ensure that all students, including those with learning disabilities, have equal opportunities to participate. By monitoring participation, educators can implement strategies to encourage engagement from quieter students or those who may need extra encouragement to speak up.
- Parental Engagement Reports: Schools can generate reports for parents that highlight their child's engagement levels in class, showing how often they raise their hand. This transparency can facilitate discussions about academic participation and the importance of being active in the classroom environment.