Titlebook: Topics in Medical Image Processing and Computational Vision; João Manuel R.S. Tavares,Renato M. Natal Jorge Book 2013 Springer Science+Bus

滔滔不绝的人

冥想后

countenance

Detection of Anatomic Structures in Retinal Images,in each of these structures. Some parameters should be extracted in order to evaluate if an eye is healthy. For example, the level of imperfection of the optic disk’s circle contour is related with glaucoma. Furthermore, the proximity of the lesion in the retina to the fovea (structure responsible f

意见一致

Database System for Clinical and Computer Assisted Diagnosis of Dermoscopy Images,erest in the development of computer assisted diagnosis systems, given their great potential to this area of medicine. The standard approach in automatic dermoscopic image analysis can be divided in three stages: image segmentation, feature extraction/selection and lesion classification. In order to

BAIL

Segmentation Based Pattern Recognition for Peri-Urban Areas in X Band SAR Images,ferent zones in peri-urban forestries integrating information from different sources. In particular the X band is sensitive to the moisture content of the ground that can be therefore put into relation with the gray level of the image; moreover, the gray level is related to the smoothness and roughn

AMBI

Improving Flood Risk Management in the City of Lisbon: Developing a Detailed and Updated Map of Imperviousness Using Satellite Imagery,nding to potential urban flooding events. Remote sensing constitutes a valuable data source to derive land cover information required for flood risk assessment. The present paper describes the generation of a Land Cover Map for the city of Lisbon, Portugal. The data source is an IKONOS-2 pansharp im

falsehood

Book 2013 Processing and Computational Vision, including: Object Recognition, Object Detection, Object Tracking, Pose Estimation, Facial Expression Recognition, Image Retrieval, Data Mining, Automatic Video Understanding and Management, Edges Detection, Image Segmentation, Modelling and Simulation, Medical t

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广大

Identification of Foliar Diseases in Cotton Crop,avelet transform for feature extraction and a Support Vector Machine for the actual classification. Five possible diagnostics are provided: (1) healthy (SA), (2) injured with Ramularia disease (RA), (3) infected with Bacterial Blight (BA), (4) infected with Ascochyta Blight (AS), or (5) possibly infected with an unknown disease.

爱管闲事

Towards Ontological Cognitive System,ifferent environments, while managing and integrating several types of knowledge. Future directions suggest to reinforce the multi-modal fusion of information sources and the communication with end-users.