YOLOv7: Real-time Object Detection with Computer Vision Training Course

This instructor-led training in Slovakia explores the deployment and optimization of CV and NLP models using the CANN SDK for Ascend hardware. Learners will master model conversion, integration into live pipelines, and strategies to boost inference performance for real-time detection and analysis.

This live, instructor-led session in Slovakia (online or onsite) targets intermediate-level AI developers and computer vision engineers aiming to build robust vision systems for autonomous driving applications.

By the end of this training, participants will be able to:

• Understand the fundamental concepts of computer vision in autonomous vehicles.
• Implement algorithms for object detection, lane detection, and semantic segmentation.
• Integrate vision systems with other autonomous vehicle subsystems.
• Apply deep learning techniques for advanced perception tasks.
• Evaluate the performance of computer vision models in real-world scenarios.

This instructor-led, live training in Slovakia (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab.

Upon completing this training, participants will be able to:

• Construct and train convolutional neural networks (CNNs) utilizing TensorFlow.
• Utilize Google Colab for scalable and efficient cloud-based model development.
• Apply image preprocessing techniques suitable for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Employ transfer learning to boost the performance of CNN models.
• Visualize and interpret the outcomes of image classification models.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level to advanced-level computer vision engineers, AI developers, and IoT professionals who wish to implement and optimize computer vision models for real-time processing on edge devices.

By the end of this training, participants will be able to:

• Understand the fundamentals of Edge AI and its applications in computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Use frameworks like TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimize AI models for performance, power efficiency, and low-latency inference.

This instructor-led, live training in Slovakia (online or onsite) is aimed at beginner-level law enforcement personnel who wish to transition from manual facial sketching to using AI tools for developing facial recognition systems.

By the end of this training, participants will be able to:

• Understand the fundamentals of Artificial Intelligence and Machine Learning.
• Learn the basics of digital image processing and its application in facial recognition.
• Develop skills in using AI tools and frameworks to create facial recognition models.
• Gain hands-on experience in creating, training, and testing facial recognition systems.
• Understand ethical considerations and best practices in the use of facial recognition technology.

This practical training module on Slovakia focuses on the core capabilities of Fiji and ImageJ for biological research. Participants will develop hands-on expertise in image preprocessing, quantitative assessment, and macro automation. These skills are essential for optimizing workflows involving histological tissues, cells, and other samples, ensuring reproducible and precise scientific results.

Explore the essentials of Computer Vision in this practical, instructor-led session held in Slovakia. Participants will utilize Python to construct robust systems for face, object, and motion detection. This program provides a solid, practice-oriented foundation in image processing and core Computer Vision techniques.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level professionals who wish to use Vision Builder AI to design, implement, and optimize automated inspection systems for SMT (Surface-Mount Technology) processes.

By the end of this training, participants will be able to:

• Set up and configure automated inspections using Vision Builder AI.
• Acquire and preprocess high-quality images for analysis.
• Implement logic-based decisions for defect detection and process validation.
• Generate inspection reports and optimize system performance.