Semantic Segmentation Courses and Certifications

DigitalSreeni

Labeling Images for Semantic Segmentation Using Label Studio

Learn to label images for semantic segmentation using Label Studio, covering installation, project setup, annotation, and exporting in this practical tutorial.

• YouTube
• 27 minutes
• On-Demand
• Free Video

DigitalSreeni

Semantic Segmentation of Aerial Imagery Using U-Net

Learn to preprocess aerial imagery, train U-net for semantic segmentation, and make predictions using Python, focusing on data preparation and model implementation for satellite image analysis.

• YouTube
• 42 minutes
• On-Demand
• Free Video

DigitalSreeni

Semantic Segmentation Made Easy - Using Segmentation Models Library

Learn to implement semantic segmentation using the Segmentation Models library, covering model types, backbones, data augmentation, preprocessing, and training on electron microscopy datasets.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Region Mutual Information Loss for Semantic Segmentation

1 review

Explore advanced techniques in semantic segmentation, including region mutual information loss, à trous convolutions, and multi-scale features for improved image analysis and understanding.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Andreas Geiger

Segmenting and Tracking Every Pixel

Explore video panoptic segmentation with STEP datasets, focusing on real-world challenges in pixel-precise segmentation and tracking. Learn about new evaluation metrics and baseline methods.

• YouTube
• 34 minutes
• On-Demand
• Free Video

MITCBMM

Towards Machines that Perceive and Communicate

Explore cutting-edge research in visual scene understanding and grounded language processing, covering semantic segmentation, object detection, and image captioning advancements.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Video

DigitalSreeni

Improving Semantic Segmentation - U-Net Performance via Ensemble of Multiple Trained Networks

Enhance U-Net performance for semantic segmentation using ensemble methods with ResNet34, Inception V3, and VGG16 networks. Includes code, dataset, and practical implementation tips.

• YouTube
• 30 minutes
• On-Demand
• Free Video

DigitalSreeni

Pretrained CNN Features for Semantic Segmentation Using Random Forest

Explore semantic segmentation using VGG16 features and Random Forest, offering improved results for limited training data compared to U-net.

• YouTube
• 22 minutes
• On-Demand
• Free Video

CAP5415 - Semantic Segmentation Part 1 - Lecture 17

Explore semantic segmentation techniques, including pretrained layers, skip connections, and upsampling methods for advanced image analysis and understanding.

• YouTube
• 48 minutes
• On-Demand
• Free Video

Coursera

Semantic Segmentation with Amazon Sagemaker

94 ratings at Coursera

Train and deploy a semantic segmentation model on Amazon SageMaker to classify pet image pixels as foreground, background, or unclassified using the IIIT-Oxford Pets Dataset.

• Coursera
• 1 hour 45 minutes
• On-Demand
• Paid Course

Modern Computer Vision & Deep Learning with Python & PyTorch

319 ratings at Udemy

Computer Vision with Python using Deep Learning for Classification, Instance and Semantic Segmentation, Object Detection

• Udemy
• 11 hours 49 minutes
• On-Demand
• Paid Course

Computer Vision For iOS Developers Course

54 ratings at Udemy

Learn how to train Object Detection and Semantic Segmentation models for mobile, and integrate them into your app.

• Udemy
• 1 hour 52 minutes
• On-Demand
• Free Online Course

Packt

Self-Driving Car Specialization Course

Master autonomous vehicle development through hands-on training in system design, control systems, computer vision, and ROS simulation. Build practical skills using Jetbot and Jetson Nano for real-world implementation.

• Coursera
• 9 hours 21 minutes
• On-Demand
• Paid Course

Packt

Mastering Image Segmentation with PyTorch

Explore image segmentation with PyTorch, from basics to advanced techniques. Learn CNNs, semantic segmentation, and tackle real-world projects to master this crucial aspect of computer vision.

• Coursera
• 6 hours 29 minutes
• On-Demand
• Paid Course

DigitalSreeni

3D U-Net for Semantic Segmentation

Learn to implement 3D U-Net for semantic segmentation on volumetric data like FIB-SEM, CT, and MRI. Covers data preparation, model architecture, training, and multichannel image processing using Python libraries.

• YouTube
• 50 minutes
• On-Demand
• Free Video