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Michael Abramov

Michael Abramov

Machine Learning

Product Recognition in Retail

Smart carts, powered by retail AI, are equipped with cameras that identify and classify products on smart shelves for better accuracy and efficiency. These advances are not theoretical. Retailers implementing AI-based solutions increase sales conversion rates and improve inventory tracking accuracy. Quick Take * Deep learning models control inventory and reduce

Computer Vision

Manufacturing Defect Detection: Annotation Techniques for Quality Control

With the increasing complexity of manufacturing processes, there is a growing reliance on advanced techniques to identify defects early in the production cycle. Annotation techniques play a pivotal role in this process by providing structured data that helps train machine learning models to detect defects automatically. These techniques involve labeling

Data Annotation

Data Augmentation Strategies: Scaling a Dataset Without Additional Annotations

Data augmentation is a technique that artificially expands datasets and creates different variations of samples without the need for additional annotations. In deep learning, data augmentation increases the amount of data, sets the limits of the AI model's solution, and improves performance. Implementing data augmentation strategies reveals the

Computer Vision

Handling Cultural and Language Nuances in Annotation Teams

When building datasets, annotation teams often come from different cultural and linguistic backgrounds. This diversity can provide valuable perspectives but also leads to differences in how people understand the same task. Language is also closely related to the local context. Annotators may understand words but not their meanings if they

Computer Vision

Annotating for OCR: Preparing Datasets for Text Extraction in Images

In the emerging field of computer vision, the ability to extract text from images has opened the door to automation, accessibility, and data-driven insights in countless industries. From digitizing handwritten archives to real-time translation using mobile devices, systems built on optical character recognition (OCR) have become more sophisticated and widespread.

Computer Vision

GDPR and Data Labeling: Best Compliance Practices for EU Markets

Organizations that process personal data understand the impact of GDPR on data protection and labeling practices. The GDPR, established in 2018, ensures data integrity and confidentiality. However, labeling personal data in a data protection-compliant manner can be challenging, especially when working with raw data. Quick Take * Accurate labeling of personal

Computer Vision

Implementing Active Learning Strategies: Label Smarter, Not Harder

Instead of randomly labeling a large dataset, active learning helps identify the most informative data points, reducing the overall labeling effort and improving model performance. Compared to traditional supervised learning, where all data points are labeled before training, active learning allows the model to request labels for only the most