Computer vision has become an essential strategy for companies looking to leverage the full potential of AI in their operations. It enables machines to perceive and analyze the visual world, paving the way for a wide range of applications, from facial recognition to autonomous driving. In this article, we will explore real-world use cases, highlight companies that have succeeded with computer vision, and show how Tchek can help you launch customized training and models tailored to your specific needs.
Mastery of Architectures and Applications
Computer vision is greatly enhanced by our expertise in Convolutional Neural Networks (CNN) and Vision Transformers. We specialize in various applications, including image classification, object detection, image segmentation, object tracking, and object re-identification. Our experience allows us to adapt these architectures to meet the specific needs of different businesses. This flexibility ensures that our solutions are not only effective but also aligned with the unique operational requirements of our clients.
Creation of Customized Solutions
One of our key strengths is the ability to create tailored architectures, such as improving object detectors for automotive inspection. Our solutions can detect, locate, and group damages across multiple images with precision. We estimate the angle and distance of objects to provide comprehensive analysis, ensuring that our models are lightweight and suited for production constraints. By employing a divide and conquer strategy, we optimize performance while minimizing complexity, leading to faster and more efficient implementations.
Data Valuation
Tchek AI focuses on optimizing data quality through published work on denoising labels, which enhances the overall dataset integrity. Our use of advanced techniques, such as meta-learning, improves data cleaning processes, making them more efficient. Additionally, we utilize self-pretraining methods (like EVA) to streamline model training, significantly reducing computational costs while enhancing performance. This commitment to data optimization ensures that our models are built on a solid foundation, maximizing their effectiveness in real-world applications.
Computer Vision Industry Example
Computer vision is experiencing exponential growth, with a global market projected to reach $24.37 billion by 2026. An increasing number of companies are adopting this technology to optimize efficiency, improve accuracy, and enhance control over their processes. Various sectors, such as healthcare, security, and manufacturing, are leveraging computer vision for applications such as:
Industry
● Quality Control: Use computer vision to inspect products for defects and ensure quality standards are met during manufacturing.
● Wrong Fabrication Detection: Identify manufacturing errors early in the production process to reduce waste and rework.
Logistics& Supply Chain
● Damage Detection: Automatically identify damages to packages during transportation, reducing losses and improving customer satisfaction.
● Inventory Management: Use computer vision to track inventory levels in real-time, minimizing human error and optimizing stock control.
Retail
● Discrimination and Inappropriate Content Moderation: Use AI to filter out offensive or discriminatory content, such as nudity or inappropriate images, in online product reviews or customer-submitted images.
● PictureEnhancement: Enhance the quality of product images for better presentation on e-commerce platforms, increasing sales conversions.
Security
● Surveillance and Movement Detection: Monitor video footage to detect unauthorized movement in secure areas, improving security response.
● FacialRecognition and ID Verification: Use facial recognition to verify identities in restricted areas, providing access control for security-sensitive environments.
