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- Agriculture
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- NLP
- OCR
- Retail
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- All Case Study
- Agriculture
- Autonomous
- Computer Vision
- Cybersecurity
- E-commerce
- Food
- Geospatial technology
- Industrial Automation
- Medical
- NLP
- OCR
- Retail
- SEO
- Sports
- Wildlife Biology
OCR
Digit Recognition Dataset- MNIST
The MNIST dataset serves as a crucial resource for advancing digit recognition algorithms, enabling the development of highly accurate and efficient models.
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Computer Vision
Anomaly Detection in IoT Sensor Data
Through this project, we have fortified the capability of IoT systems in anomaly detection
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Computer Vision
Parcel Videos Data Collection
The Parcel Videos Data Collection Initiative is poised to revolutionize the logistics and e-commerce industries.
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Autonomous
Walkway Segmentation Dataset
The Walkway Segmentation Dataset acts as a linchpin for.
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NLP
Global Event and Language Tone Dataset
Global Event and Language Tone Dataset Project Overview: Objective The ...
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Agriculture
Image Annotation for Agricultural Yield Prediction
In the context of agricultural yield prediction, image annotation proves.
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OCR
Language Identification for Multilingual Content
Language identification for multilingual content plays a pivotal role in bridging linguistic barriers and enhancing user experience
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Autonomous
Vehicle Driving Behaviors Video Dataset
The Vehicle Driving Behaviors Video Dataset stands as a keystone in the.
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Computer Vision
Remote Sensing Image Dataset
EuroSAT stands as an invaluable asset for advancing research and applications in remote sensing and Earth observation.
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SEO
Face Detection in Photos for Social Media Apps
Face detection in photos is a transformative feature for social media apps, enhancing user experience and privacy in various ways.
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Computer Vision
Alexa Wake Words in EU Spanish (Youth)
This project exemplifies our capability in handling large-scale data collection and annotation tasks with precision and efficiency.
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Computer Vision
Indoor Scene Recognition Dataset
The Indoor Scene Recognition Dataset derived from the SUN Database represents a significant resource for advancing research in indoor scene understanding and recognition.
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