{"product_id":"hypothesis-based-image-segmentation-a-machine-learning-approach-von-alexander-denecke","title":"Hypothesis-based image segmentation","description":"\u003cp\u003eThis thesis addresses the ¿gure-ground segmentation problem in the context of complex systems for automatic object recognition. Firstly the problem of image segmentation in general terms is introduced, followed by a discussion about its importance for online and interactive acquisition of visual representations. Secondly a machine learning approach using arti¿cial neural networks is presented. This approach on the basis of Generalized Learning Vector Quantization is investigated in challenging scenarios such as the real-time ¿gure-ground segmentation of complex shaped objects under continuously changing environment conditions. The ability to ful¿ll these requirements characterize the novelty of the approach compared to state-of-the-art methods. Finally the proposed technique is extended in several aspects, which yields a framework for object segmentation that is applicable to improve current systems for visual object learning and recognition.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783838133713\"\u003e\u003ch3\u003eA Machine Learning Approach\u003c\/h3\u003e\u003c\/div\u003e","brand":"Libri","offers":[{"title":"Softcover - 9783838133713","offer_id":39440977526877,"sku":"9783838133713","price":79.9,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/f044ac23-1afe-4ddc-95d8-92d68ad77e79.jpg?v=1777956923","url":"https:\/\/shop.autorenwelt.de\/en\/products\/hypothesis-based-image-segmentation-a-machine-learning-approach-von-alexander-denecke","provider":"Autorenwelt Shop","version":"1.0","type":"link"}