What first comes to mind when you hear “computer vision“? We bet it's “deep learning“ or “neural networks“, right? This is understandable: neural networks are already able to generate images according to text descriptions, break records in image recognition and segmentation, and solve many problems in general. But does this mean that the time of classical image processing algorithms is coming to an end? Deep Learning methods require both large amounts of learning data and powerful computing resources. Can the classics help here? Of course! The correct use of classical methods has a positive effect on both the accuracy and efficiency of the developed solutions. At It-Jim's webinar “Computer vision: DL or not DL?“, the company experts analyze the balance of the use of classical image processing algorithms and modern methods based on deep learning on specific examples of Computer Vision tasks. 🔊 Speakers: Pavlo Vyplavin, CTO at It-Jim, Ph.D. Pavlo knows everything about signal processing, classic CV algorith
Hide player controls
Hide resume playing