コンピュータビジョンの基礎（271～300）– コンピュータビジョンの基本概念と手法を学びます。 –

Recap and Today's Theme Hello! In the previous episode, we covered transfer learning, where we leveraged pre-trained models (like VGG16) and adapted them for new image classification tasks. Transfer learning allowed us to build high-accu...

Recap and Today's Theme Hello! In the previous episode, we discussed data augmentation, which improves model performance even with limited data by using techniques such as rotation, shifting, and noise addition. Today, we will dive into ...

Recap and Today's Theme Hello! In the previous episode, we explained how to build image classification models using CNNs (Convolutional Neural Networks). Using the handwritten digit dataset (MNIST) as an example, we learned how to classi...

Recap and Today's Theme Hello! In the previous episode, we explained feature extraction methods like SIFT, SURF, and ORB for detecting key points in images. While these techniques are effective for object recognition and pattern matching...

Recap and Today's Theme Hello! In the previous episode, we discussed template matching, a fundamental technique for detecting specific patterns in images. Template matching is widely applied in object recognition, quality inspection, and...

Recap and Today's Theme Hello! In the previous episode, we discussed image binarization, a fundamental technique for converting images into two-tone (black and white) representations. This method is widely used in applications such as ob...

Recap and Today's Theme Hello! In the previous episode, we discussed image histograms and how to visualize the distribution of brightness and color in an image. This time, we’ll cover image binarization, a fundamental operation in image ...

Recap and Today's Theme Hello! In the previous episode, we discussed edge detection techniques, including the Sobel and Canny methods. Today, we will focus on image histograms, an essential tool in image processing that visually represen...

Recap and Today's Theme Hello! In the previous episode, we explained the basics of convolution and how filters are used in image processing. This time, we will introduce an important technique in image processing: edge detection. Edge de...

Recap and Today's Theme Hello! In the previous episode, we discussed image preprocessing, where we learned how to resize, normalize, filter, and augment images. Today, we will delve into the foundational operation in image processing and...

Recap and Today's Theme Hello! In the previous episode, we introduced OpenCV and learned how to perform basic operations like loading, displaying, resizing, and color space conversion. Today, we will discuss the important topic of image ...

Recap and Today's Theme Hello! In the previous episode, we explained how to handle image data. We covered the basics of pixel data and learned how to load images using Python. In this episode, we will introduce OpenCV, a powerful library...

Recap and Today's Theme Hello! In the previous episode, we introduced the concept of Computer Vision and discussed how to extract information from images and videos. Today, we will learn about how to handle image data, focusing on the co...

Recap and Today's Theme Hello! In the previous episode, we reviewed Chapter 9 and conducted a knowledge check to deepen our understanding of Natural Language Processing (NLP). Now, we’re entering Chapter 10, where we will start learning ...