Gajanan Kale (59 results)

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: New.

paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Taschenbuch. Condition: Neu. Un seuillage optimal à plusieurs niveaux pour la segmentation d'images en couleur | Gajanan Kale (u. a.) | Taschenbuch | Französisch | 2023 | Editions Notre Savoir | EAN 9786206671237 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Taschenbuch. Condition: Neu. Una soglia multilivello ottimale per la segmentazione di immagini a colori | Gajanan Kale (u. a.) | Taschenbuch | Italienisch | 2023 | Edizioni Sapienza | EAN 9786206671244 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. Uma limiarização multinível óptima baseada na segmentação de imagens a cores | Gajanan Kale (u. a.) | Taschenbuch | Portugiesisch | 2023 | Edições Nosso Conhecimento | EAN 9786206671176 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. Optimale mehrstufige Schwellenwertbildung für die Segmentierung von Farbbildern | Gajanan Kale (u. a.) | Taschenbuch | 76 S. | Deutsch | 2023 | Verlag Unser Wissen | EAN 9786206671213 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable invasive cancer diagnosis solution. With minimum annotation information, the proposed method mines contrast patterns between normal and malignant images in unsupervised manner and generates a probability map of abnormalities to verify its reasoning. Particularly, a fully convolutional autoencoder is used to learn the dominant structural patterns among normal image patches. Patches that do not share the characteristics of this normal population are detected and analyzed by one-class support vector machine and 1-layer neural network. We apply the proposed method to a public breast cancer image set. Ourresults, in consultation with a senior pathologist, demonstrate that the proposed method outperforms existing methods. The obtained probability map could benefit the pathology practice by providing visualized verification data and potentially leads to a better understanding of data-driven diagnosis solutions. 76 pp. Englisch.…

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -El diagnóstico preciso del cáncer de mama en imágenes de histopatología es un desafío debido a la heterogeneidad del crecimiento de las células cancerosas, así como a una variedad de lesiones proliferativas benignas del tejido mamario. En este trabajo proponemos una solución de diagnóstico de cáncer invasivo práctica y autointerpretable. Con información de anotación mínima, el método propuesto extrae patrones de contraste entre imágenes normales y malignas de manera no supervisada y genera un mapa de probabilidad de anomalías para verificar su razonamiento. En particular, se utiliza un codificador automático totalmente convolucional para aprender los patrones estructurales dominantes entre los parches de imágenes normales. Los parches que no comparten las características de esta población normal se detectan y analizan mediante una máquina de vectores de soporte de una clase y una red neuronal de una capa. Aplicamos el método propuesto a un conjunto de imágenes públicas de cáncer de mama. Nuestros resultados, en consulta con un patólogo experimentado, demuestran que el método propuesto supera a los métodos existentes. El mapa de probabilidad obtenido podría beneficiar la práctica de patología al proporcionar datos de verificación visualizados y potencialmente conducir a una mejor comprensión de las soluciones de diagnóstico basadas en datos. 76 pp. Spanisch.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Multimedia applications have very stringent Quality of Service (QoS) demands and require a connection oriented service. For these applications, a path satisfying their requirements in terms of bandwidth, delay, buffer etc.The goal of QoS routing algorithms is to find a loop-less path satisfying a given set of constraints on parameters like bandwidth, delay, etc. The path selection process could return either the entire path to the destination or the best next hop for the request.The first case is called as Source routing and the second is referred to as distributed routing, Proposed system uses a new distributed QoS routing algorithm for unicast flows, which has a very low call establishment overhead. QoS routing algorithm makes use of existing IP routing protocols like OSPF, RIP with minimal modifications. …

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this work, we propose a practical and self interpretable invasive cancer diagnosis solution. With minimum annotation information, the proposed method mines contrast patterns between normal and malignant images in unsupervised manner and generates a probability map of abnormalities to verify its reasoning. Particularly, a fully convolutional autoencoder is used to learn the dominant structural patterns among normal image patches. Patches that do not share the characteristics of this normal population are detected and analyzed by one-class support vector machine and 1-layer neural network. We apply the proposed method to a public breast cancer image set. Ourresults, in consultation with a senior pathologist, demonstrate that the proposed method outperforms existing methods. The obtained probability map could benefit the pathology practice by providing visualized verification data and potentially leads to a better understanding of data-driven diagnosis solutions. …