1,721,234 research outputs found
An Outline of Italian Leptobos and a first sight on Leptobos aff. vallisarni from Pietrafitta (Early Pleistocene, Perugia).
No full textA hierarchical classification system for object recognition in underwater environments
No full textIn this paper, a hierarchical system, in which each level is composed by a neural-based classifier, is proposed to recognize objects in underwater images. The system has been designed to help an autonomous underwater vehicle in sea-bottom survey operations, like pipeline inspections. The input image is divided into square regions (macro-pixels) and a neural tree is used to classify each region into different object classes (pipeline, sea-bottom, or anodes). Each macro-pixel is then analyzed according to some geometric and environment constraints: macro-pixels with doubt classification are divided into four parts and re-classified. The process is iterated until the desired accuracy is reached. Experimental results, which have been performed on a large set of real underwater images acquired in different sea environments, demonstrate the robustness and the accuracy of the proposed system
Noise robust and invariant object classification by the high-order statistical pattern spectrum
No full textA new shape descriptor, the high order statistical pattern spectrum (HSP), able to extract from real images a set of descriptive features which can be used to classify objects regardless of their positions, sizes, orientations and the presence of noise, has been developed. The HSP is an internal, noise-robust, noninformation-preserving operator which combines the properties of invariance of the high order pattern spectrum and the properties of noise robustness of the statistical pattern spectrum. A neural network trained by a back-propagation algorithm has been used to test the method on different classification problems. Experimental results are presented on both synthetic and real images corrupted by various levels of noise and containing an object in different positions. Comparisons with other existing shape descriptor operators have been also performed
A vision based system for object detection in underwater images
No full textIn this paper, a vision-based system for underwater object detection is presented. The system is able to detect automatically a pipeline placed on the sea bottom, and some objects, e.g. trestles and anodes, placed in its neighborhoods. A color compensation procedure has been introduced in order to reduce problems connected with the light attenuation in the water. Artificial neural networks are then applied in order to classify in real-time the pixels of the input image into different classes, corresponding e.g. to different objects present in the observed scene. Geometric reasoning is applied to reduce the detection of false objects and to improve the accuracy of true detected objects. The results on real underwater images representing a pipeline structure in different scenarios are shown. The presence of seaweed and sand, different illumination conditions and water depth, different pipeline diameter and small variations of the camera tilt angle are considered to evaluate the algorithm performances
Cultura della razza e cultura letteraria nell'Italia del Novecento
No full textNel volume, che riprende, con significative integrazioni, gli interventi di un Convegno tenutosi nella Università di Roma "Tor Vergata" e alla Sapienza Università di Roma in occasione dei 70 anni dalla promulgazione delle Leggi razziali, si indaga l'impatto che la concezione dell'individuo come esponente di una "razza" ha avuto nella cultura e nella letteratura dell'Italia durante il Novecento
- …
