Computer Vision Training in Nepal

This instructor-led, live training in Nepal (online or onsite) is aimed at intermediate to advanced 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 Nepal (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.

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

• Build and train convolutional neural networks (CNNs) using TensorFlow.
• Leverage Google Colab for scalable and efficient cloud-based model development.
• Implement image preprocessing techniques for computer vision tasks.
• Deploy computer vision models for real-world applications.
• Use transfer learning to enhance the performance of CNN models.
• Visualize and interpret the results of image classification models.

This instructor-led, live training in Nepal (online or onsite) is aimed at intermediate-level AI developers and computer vision engineers who wish to build robust vision systems for autonomous driving applications.

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

• Grasp 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 Nepal (offered online or on-site) is targeted at beginner-level law enforcement staff seeking to transition from manual facial sketching to utilizing AI tools for developing facial recognition systems.

By the conclusion 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 hands-on training in Nepal provides a comprehensive overview of Fiji and ImageJ fundamentals tailored for biological research. Participants will develop practical skills in image preprocessing, quantitative analysis, and macro automation, enabling them to streamline workflows for histological tissues, cells, and other samples while ensuring reproducible results.

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

Upon completing this training, participants will be equipped to:

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

This live, instructor-led training in Nepal, offered online or onsite, is designed for intermediate to advanced developers, researchers, and data scientists aiming to implement real-time object detection using YOLOv7.

By the end of the program, participants will be able to:

• Comprehend the essential concepts of object detection.
• Install and configure YOLOv7 for detection workflows.
• Train and validate custom object detection models with YOLOv7.
• Connect YOLOv7 with additional computer vision frameworks and utilities.
• Address typical issues arising in YOLOv7 implementation.