Computer Vision, a prominent field within computer science, aims to replicate aspects of the human visual system, enabling computers to identify and process objects in images and videos much like humans do.
Amzur’s Computer Vision solutions incorporate core Machine Learning concepts, already integrated into various major products, such as social media AR filters, automated traffic cameras, and defect detection in manufacturing.
Image classification is the process of assigning a category to an image. This can be done manually, but it can be time-consuming and error-prone. Computer vision can automate image classification, which can free up employees to focus on other tasks.
Image segmentation is the process of dividing an image into its constituent parts. This can be used to identify objects in an image, or to extract specific features from an image. Computer vision can automate image segmentation, which can be used for a variety of applications, such as medical diagnostics, robotics, and video surveillance.
Object detection is the process of identifying and locating objects in an image or video. This can be used for a variety of applications, such as facial recognition, crowd counting, and anomaly detection. Computer vision can automate object detection, which can be used to improve the efficiency and accuracy of these applications.
Object tracking is the process of identifying and tracking the movement of objects in an image or video. This can be used for a variety of applications, such as video surveillance, traffic monitoring, and robotics. Computer vision can automate object tracking, which can be used to improve the efficiency and accuracy of these applications.
Pose estimation is the process of estimating the pose of an object or person in an image or video. This can be used for a variety of applications, such as human-computer interaction, sports analytics, and robotics. Computer vision can automate pose estimation, which can be used to improve the accuracy and efficiency of these applications.
We develop and deploy highly advanced generative adversarial network (GAN) models – AI neural systems that can generate impressively realistic synthetic data including images, text, video, and music. Through machine learning innovation and optimization, our GAN models can enhance, augment, or fabricate media with precision in a scalable way.
Amzur’s computer vision solutions offer a number of benefits, including:
Enhanced Accuracy and Efficiency
With computer vision, we can process and analyze visual data more quickly and accurately than humans, reducing errors and increasing efficiency in various tasks such as inspection, sorting, and quality control.
Automated Real-Time Analysis
With the ability to analyze visual data in real time, computer vision enables immediate decision-making and action, such as identifying defects on a production line or monitoring security footage for unusual activities.
Computer vision provides valuable insights by analyzing visual data trends, which can inform business strategies, market research, and customer behavior analysis across various industries.
Enhanced Customer Experience
In retail, hospitality, and other service industries, computer vision can enhance customer experience through personalized recommendations, faster checkouts, and improved service quality.
What we do
Our end-to-end computer vision enablement services, spanning consulting, training, and ongoing support, guide partners seamlessly from education to adoption and ongoing optimization. Initial consultations ensure appropriate solution scoping and priority capability alignment. Robust training programs focused on both technical users and business decision makers then facilitate proficient management so that deployed CV systems sustainably deliver ROI. Throughout ongoing operations, our hands-on support team troubleshoots issues, provides upgrade guidance, and continually aligns algorithm performance to evolving business objectives through fine-tuning. Partners rely on us for the entire computer vision lifecycle – from strategic planning to daily enhancements.
Auto-Moderation of User Generated Content
A European e-commerce client used our NLP pipelines and machine learning models to automate content moderation, resulting in a reduction of manual moderation efforts and improved data security, with almost full precision detection of PII and blacklisted items, and cost reduction due to migration to a new database.
Automated Technician Recommender Platform
A California-based HVAC servicing company used AI to develop a recommendation engine that automates the process of assigning technicians to service requests. The recommendation engine has helped the company to improve its efficiency and customer satisfaction.
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