{"product_id":"automatic-extraction-of-vector-representations-of-line-features-von-ahmed-el-harby","title":"Automatic extraction of vector representations of line features","description":"\u003cp\u003eThis book describes the development and evaluation  of a system that can classify line features from  remotely sensed images in raster format using neural  networks and transform the classified features into  vector representations automatically using a new  Square Scan Algorithm (SSA). The SSA was designed to  deal with branching and crossing lines in order to  transfer the line features in raster images into  vector representations automatically. This algorithm  was tested and it was found that the algorithm could  successfully remove most noise pixels and detect  branching, crossing, and isolated lines. In  addition, it connected disconnected lines that have  a small gap between them. A new method was proposed  to collect the training data automatically from new  images that depended on the neural network results. The above approach was applied for continuous  classification from new images over time by  selecting the training data positions automatically.  This book helps students to apply neural networks  for classifying features and to understand the  automatic extraction process of vector  representations of line features from remotely  sensed images.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783838339627\"\u003e\u003ch3\u003eClassifying from remotely sensed images\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9783838339627","offer_id":39469157777501,"sku":"9783838339627","price":79.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/0776cafd-6d1a-4206-84d9-c666e5b11abf.jpg?v=1758089255","url":"https:\/\/shop.autorenwelt.de\/products\/automatic-extraction-of-vector-representations-of-line-features-von-ahmed-el-harby","provider":"Autorenwelt Shop","version":"1.0","type":"link"}