Autonomous learning of semantic segmentation from Internet images

A Hybrid Algorithm based on Deep Learning and Restricted Boltzmann Machine for Car Semantic Segmentation from Unmanned Aerial Vehicles (UAVs)-based Thermal Infrared Images

Nowadays, ground vehicle monitoring (GVM) is one of the areas of application in the intelligent traffic control system using image processing methods. In this context, the use of unmanned aerial vehicles based on thermal infrared (UAV-TIR) images is one of the optimal options for GVM due to the suitable spatial resolution, cost-effective and low volume of images. The methods that have been prop...

WebSeg: Learning Semantic Segmentation from Web Searches

In this paper, we improve semantic segmentation by automatically learning from Flickr images associated with a particular keyword, without relying on any explicit user annotations, thus substantially alleviating the dependence on accurate annotations when compared to previous weakly supervised methods. To solve such a challenging problem, we leverage several low-level cues (such as saliency, ed...

Multi Resolution Fuzzy Segmentation of Satellite Images

Semantic Segmentation of Street-Side Images

In this paper we propose a method for semantic segmentation of street-side images. Segmentation and classification is pixel based and results in classes of building facades, sections of sky, road and other areas present in general images taken in the urban environment. A segmentation method is suggested and detected segments are classified. Final classification is reinforced using context infor...

Neural Network-Based Learning Kernel for Automatic Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Images

Background: Multiple Sclerosis (MS) is a degenerative disease of central nervous system. MS patients have some dead tissues in their brains called MS lesions. MRI is an imaging technique sensitive to soft tissues such as brain that shows MS lesions as hyper-intense or hypo-intense signals. Since manual segmentation of these lesions is a laborious and time consuming task, automatic segmentation ...