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Semantic Segmentation for Urban Planning Maps based on U-Net

arXiv.org Machine Learning

The automatic digitizing of paper maps is a significant and challenging task for both academia and industry. As an important procedure of map digitizing, the semantic segmentation section mainly relies on manual visual interpretation with low efficiency. In this study, we select urban planning maps as a representative sample and investigate the feasibility of utilizing U-shape fully convolutional based architecture to perform end-to-end map semantic segmentation. The experimental results obtained from the test area in Shibuya district, Tokyo, demonstrate that our proposed method could achieve a very high Jaccard similarity coefficient of 93.63% and an overall accuracy of 99.36%. For implementation on GPGPU and cuDNN, the required processing time for the whole Shibuya district can be less than three minutes. The results indicate the proposed method can serve as a viable tool for urban planning map semantic segmentation task with high accuracy and efficiency.


rois-codh/kaokore

#artificialintelligence

Read the paper to learn more about Kaokore dataset, our motivations in making them, as well as creative usage of it! KaoKore is a novel dataset of face images from Japanese illustrations along with multiple labels for each face, derived from the Collection of Facial Expressions. KaoKore dataset is build based on the Collection of Facial Expressions, which results from an effort by the ROIS-DS Center for Open Data in the Humanities (CODH) that has been publicly available since 2018. It provides a dataset of cropped face images extracted from Japanese artworks publicly available from National Institute of Japanese Literature, Kyoto University Rare Materials Digital Archive and Keio University Media Center from the Late Muromachi Period (16th century) to the Early Edo Period (17th century) to facilitate research into art history, especially the study of artistic style. It also provides corresponding metadata annotated by researchers with domain expertise.


Neural Style Transfer: Creating Art with Deep Learning using tf.keras and eager execution

#artificialintelligence

In this tutorial, we will learn how to use deep learning to compose images in the style of another image (ever wish you could paint like Picasso or Van Gogh?). This is known as neural style transfer! This is a technique outlined in Leon A. Gatys' paper, A Neural Algorithm of Artistic Style, which is a great read, and you should definitely check it out. Neural style transfer is an optimization technique used to take three images, a content image, a style reference image (such as an artwork by a famous painter), and the input image you want to style -- and blend them together such that the input image is transformed to look like the content image, but "painted" in the style of the style image. For example, let's take an image of this turtle and Katsushika Hokusai's The Great Wave off Kanagawa: Now how would it look like if Hokusai decided to add the texture or style of his waves to the image of the turtle?


To 'read' this fashion magazine, you'll need a smartphone app

AITopics Original Links

Persona is one of the latest fashion magazines in Tokyo. It's printed on heavy stock paper and is full of photos of models and clothing. The only thing missing is text. An app recognizes the images, queries a cloud database and then downloads related information such as pricing and availability of dresses. Other photos feature images of tomatoes and wine, triggering a related vegetable delivery service and wine retailer, as well as online coupons.


Image analysis reveals North Korea may have planned to send first ICBM test much closer to Japan

The Japan Times

What does a barely readable map on the desk of North Korean leader Kim Jong Un in a propaganda photo say about Pyongyang's increasingly capable missile and nuclear weapons programs and how Japan fits into its military doctrine? A lot, it turns out. A new imagery analysis obtained exclusively by The Japan Times sheds some light on how the North views Japan and Tokyo's American protector as it seeks to master the technology needed to mount a nuclear warhead on a long-range missile capable of striking anywhere in the United States, a goal it inched closer to Friday with a second successful intercontinental ballistic missile test. One image, taken from the North's July 4 launch of the Hwasong-14 (HS-14) -- its first ICBM -- shows Kim observing the test through binoculars, his elbows planted firmly on a wooden desk with a virtually unreadable map of the missile's trajectory spread across it. Indecipherable to some, the photo languished as just one of scores of propaganda shots dispersed by the regime.