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AI for Computer Vision

Our software R&D consultancy has extensive experience in artificial intelligence, specializing in computer vision. We believe that Computer Vision has the potential to revolutionize many industries, and we are dedicated to creating accurate and efficient models that can detect and analyze visual data using machine learning methods, such as deep learning. Our expertise allows us to provide customized solutions tailored to our client’s needs, whether automating a process or developing a new product. From concept development to product delivery, our team of skilled engineers uses the latest techniques to ensure top-quality, scalable, and reliable work.  

Benefits

Let’s review some of the benefits you can acquire from the implementation of Computer Vision into your business. We can develop custom generative AI models for you, tailored for your specific use case, allowing you to gain the upper hand and build a competitive advantage over those who can only rely on readily available AI models and open-source data augmentation pipelines. 

Amongst others, we are knowledgeable in the following fields: 

  • object detection and recognition 

  • multi-view object tracking 

  • motion estimation via optical flow 

  • gesture recognition 

  • anomaly detection 

  • image generation 

  • image processing 

  • image segmentation 

  • face recognition 

ai computer vision

We use PyTorch and TensorFlow to solve computer vision problems as commonly used deep learning frameworks for developing and training neural networks. They allow us to build models for tasks such as image classification, object detection, and segmentation. OpenCV is also a popular computer vision library our engineers use for various tasks, such as image and video processing, feature detection, and object tracking. It provides an extensive collection of functions and algorithms that can be used in Python, C++, and other programming languages. C++ is often used for computer vision applications due to its speed and efficiency, allowing us to quickly process large amounts of data. And we use CUDA, a parallel computing platform and programming model that can be used with NVIDIA GPUs to accelerate the processing of deep learning models and other computationally intensive tasks in computer vision. By combining these tools and technologies, we can develop and deploy high-performance computer vision applications that can analyze and make real-time decisions based on visual data. 

Applications, Case Studies, Articles 

To validate or review our previous works in this field, feel free to check our recent projects: 

Reviews

Our hard work has been reflected in the excellent reviews we have received from our clients on multiple platforms as well as in being chosen the “Software Consultancy of the Year” by the Corporate Live Wire Awards/Magazine. See some of our achievements through Clutch or check out the client testimonials on our website.

ai computer vision

„They showed enormous skill and vast domain knowledge. We would recommend TechnoLynx to anyone looking for promptness, quality work and IT expertise.“ 

Markus Kopf - CTO, Co-Founder @ Teraki 

Industries and Applications

Our AI Computer Vision services can be applied to a wide range of industries or applications. Some computer vision examples can be:

Manufacturing

Computer Vision can automate quality control, defect detection, and assembly line optimization. 

Architecture and Construction

We can deliver various solutions that can be used for tasks such as detecting structural defects and automating the construction process. 

Finance

Computer Vision can automate document processing and fraud detection. 

Smart Retail

We can help retailers improve their supply chain management and optimize in-store layouts.  

Agriculture

Computer vision can detect crop diseases and monitor crop health.  

Aerospace

Computer vision can be used in manufacturing in Aerospace for quality control and inspection of aircraft components. 

Autonomous Vehicles

Computer vision can be used in autonomous vehicles for object detection, lane detection, and pedestrian detection. 

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