9786202060417 - Offline Handwritten Signature Verification Method: Based on Artificial Immune Recognition System and Artificial Neural Network by Sharma, Reecha; Kaur, Jasmeet (6 results)

Paperback. Condition: Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock.

Taschenbuch. Condition: Neu. Offline Handwritten Signature Verification Method | Based on Artificial Immune Recognition System and Artificial Neural Network | Reecha Sharma (u. a.) | Taschenbuch | 72 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202060417 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Natural immune system offers several fascinating options that motivated the planning of Artificial Immune Systems (AIS) accustomed solve varied issues of engineering and Artificial Intelligence (AI). AIS are significantly thriving in fault detection and diagnosing applications where anomalies like errors and failures are assimilated to viruses that ought to be detected. Thereby, AIS appear appropriate to automatically discover forgeries in signature verification systems. This work proposes a technique for offline signature verification that's supports the artificial Immune Recognition System (AIRS) and Artificial Neural Network (ANN) utilized in verification stage. For feature generation, two totally different descriptors are projected to get signature traits. the primary is that the Gaussian pyramid used for texture synthesis that is very redundant, coarse scales offer a lot of the data within the finer scales and Laplacian pyramid Seamlessly stitch along images into an image plaid (i.e., register the photographs and blurring the boundary), by smoothing the boundary in a very scale-dependent style to avoid boundary artefacts. 72 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharma ReechaDr Reecha Sharma is working as Assistant Professor in Deptt of ECE Punjabi University Patiala, India. She has eleven years of teaching experience. She has published more than 60 research papers in International/ National.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Natural immune system offers several fascinating options that motivated the planning of Artificial Immune Systems (AIS) accustomed solve varied issues of engineering and Artificial Intelligence (AI). AIS are significantly thriving in fault detection and diagnosing applications where anomalies like errors and failures are assimilated to viruses that ought to be detected. Thereby, AIS appear appropriate to automatically discover forgeries in signature verification systems. This work proposes a technique for offline signature verification that's supports the artificial Immune Recognition System (AIRS) and Artificial Neural Network (ANN) utilized in verification stage. For feature generation, two totally different descriptors are projected to get signature traits. the primary is that the Gaussian pyramid used for texture synthesis that is very redundant, coarse scales offer a lot of the data within the finer scales and Laplacian pyramid Seamlessly stitch along images into an image plaid (i.e., register the photographs and blurring the boundary), by smoothing the boundary in a very scale-dependent style to avoid boundary artefacts.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Natural immune system offers several fascinating options that motivated the planning of Artificial Immune Systems (AIS) accustomed solve varied issues of engineering and Artificial Intelligence (AI). AIS are significantly thriving in fault detection and diagnosing applications where anomalies like errors and failures are assimilated to viruses that ought to be detected. Thereby, AIS appear appropriate to automatically discover forgeries in signature verification systems. This work proposes a technique for offline signature verification that's supports the artificial Immune Recognition System (AIRS) and Artificial Neural Network (ANN) utilized in verification stage. For feature generation, two totally different descriptors are projected to get signature traits. the primary is that the Gaussian pyramid used for texture synthesis that is very redundant, coarse scales offer a lot of the data within the finer scales and Laplacian pyramid Seamlessly stitch along images into an image plaid (i.e., register the photographs and blurring the boundary), by smoothing the boundary in a very scale-dependent style to avoid boundary artefacts.