Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Chandrabose, Aravindan"'
Annotated images and ground truth for the diagnosis of rare and novel diseases are scarce. This is expected to prevail, considering the small number of affected patient population and limited clinical expertise to annotate images. Further, the freque
Externí odkaz:
http://arxiv.org/abs/2210.16954
Melanoma, a malignant form of skin cancer is very threatening to life. Diagnosis of melanoma at an earlier stage is highly needed as it has a very high cure rate. Benign and malignant forms of skin cancer can be detected by analyzing the lesions pres
Externí odkaz:
http://arxiv.org/abs/1703.04364
Skin cancer is the most common of all cancers and each year million cases of skin cancer are treated. Treating and curing skin cancer is easy, if it is diagnosed and treated at an early stage. In this work we propose an automatic technique for skin l
Externí odkaz:
http://arxiv.org/abs/1703.04301
Publikováno v:
IET Computer Vision, Vol 12, Iss 8, Pp 1088-1095 (2018)
Skin cancer is the most common type of cancer in the world and the incidents of skin cancer have been rising over the past decade. Even with a dermoscopic imaging system, which magnifies the lesion region, detecting and classifying skin lesions by vi
Externí odkaz:
https://doaj.org/article/62dd07451f5b46b892a3652d8ecdbf50
Publikováno v:
Multimedia Tools and Applications. 82:15763-15778
A powerful medical decision support system for classifying skin lesions from dermoscopic images is an important tool to prognosis of skin cancer. In the recent years, Deep Convolutional Neural Network (DCNN) have made a significant advancement in det
Autor:
Chandrabose Aravindan, P. Vasuki
Publikováno v:
Journal of Experimental & Theoretical Artificial Intelligence. 33:451-466
Recognition of emotion in speech is a difficult task due to many speaker factors like gender, age, and the cultural background (nationality, ethnicity, and region) as well as the acoustical environ...
Autor:
Agerri, Rodrigo, Aliprandi, Carlo, Alkhalifa, Rabab, Alzetta, Chiara, Angel, Jason, Anselmi, Guido, Appiah Balaji, Nitin Nikamanth, Aroyehun, Segun Taofeek, Artigas Herold, Maria Fernanda, Attanasio, Giuseppe, Attardi, Giuseppe, Badryzlova, Yulia, Bai, Yang, Baldissin, Gioia, Ballarè, Silvia, Barrón-Cedeño, Alberto, Bartle, Anna-Sophie, Basile, Pierpaolo, Basile, Valerio, Basili, Roberto, Belotti, Federico, Bennici, Mauro, Bharathi, B., Bhuvana, J., Bianchi, Federico, Bisconti, Elia, Bolanos, Luis, Bondielli, Alessandro, Bosco, Cristina, Breazzano, Claudia, Brivio, Matteo, Brunato, Dominique, Cafagna, Michele, Caputo, Annalina, Caselli, Tommaso, Cassotti, Pierluigi, Castañeda, Enrique, Castro Castro, Daniel, Centeno, Roberto, Cercel, Dumitru-Clementin, Cerruti, Massimo, Chandrabose, Aravindan, Chesi, Cristiano, Chiarello, Filippo, Cignarella, Alessandra Teresa, Cimino, Andrea, Comandini, Gloria, Croce, Danilo, Dai, Hongbing, Dascalu, Mihai, Dell’Orletta, Felice, Delmonte, Rodolfo, Deng, Tao, De Francesco, Nazareno, De Martino, Graziella, De Mattei, Lorenzo, Di Buccio, Emanuele, Di Maro, Maria, di Nuovo, Elisa, Di Rosa, Emanuele, dos S.R. da Silva, Adriano, Durante, Alberto, El Abassi, Samer, Espinosa, María S., Fabrizi, Samuel, Fantoni, Gualtiero, Ferilli, Stefano, Ferraccioli, Federico, Fersini, Elisabetta, Finos, Livio, Fiorucci, Stefano, Fontana, Michele, Frenda, Simona, Gambino, Giuseppe, Gatt, Albert, Gelbukh, Alexander, Giorgi, Giulia, Giorgioni, Simone, Girardi, Paolo, Goria, Eugenio, Gregori, Lorenzo, Hoffmann, Julia, Iacono, Maria, Iovine, Andrea, Izzi, Giovanni Luca, Jimenez, Sergio, Kaiser, Jens, Kayalvizhi, S., Kivlichan, Ian, Klaus, Svea, Koceva, Frosina, Kovács, György, Kruschwitz, Udo, Labadie Tamayo, Roberto, Lai, Mirko, Laicher, Severin, Lapesa, Gabriella, Lavergne, Eric, Lebani, Gianluca E., Lees, Alyssa, Lenci, Alessandro, Leonardelli, Elisa, Li, Hongling, Liakata, Maria, Lovetere, Marco, Madonna, Domenico, Massidda, Riccardo, Mattei, Lorenzo De, Mauri, Caterina, Mele, Francesco, Melucci, Massimo, Menini, Stefano, Miaschi, Alessio, Miliani, Martina, Moggio, Alessio, Montagnani, Matteo, Montefinese, Maria, Montemagni, Simonetta, Monti, Johanna, Moraca, Maurizio, Moretti, Giovanni, Morra, Simone, Murphy, Killian, Muti, Arianna, Nakov, Preslav, Nisioi, Sergiu, Nissim, Malvina, Nozza, Debora, Occhipinti, Daniela, Ortega Bueno, Reynier, Ou, Xiaozhi, Palmonari, Matteo, Parizzi, Andrea, Pascucci, Antonio, Passaro, Lucia C., Pastor, Eliana, Patti, Viviana, Pirrone, Roberto, Polignano, Marco, Politi, Marcello, Pont, Mattia Da, Pražák, Ondřej, Přibáň, Pavel, Proisl, Thomas, Puccetti, Giovanni, Radicioni, Daniele P., Rama, Ilir, Rambelli, Giulia, Ravelli, Andrea Amelio, Rodrigo, Alvaro, Rodriguez-Diaz, Carlos A., Rodriguez Cisnero, Mariano Jason, Roman, Norton T., Roman, Norton Trevisan, Rossmann, Daniela, Rosso, Paolo, Rotaru, Armand Stefan, Rubino, Edoardo, Russo, Irene, Sabella, Gianluca, Saini, Rajkumar, Salman, Samir, Sangati, Federico, Sanguinetti, Manuela, Sarti, Gabriele, Schlechtweg, Dominik, Schulte im Walde, Sabine, Sciandra, Andrea, Setpal, Jinen, Siciliani, Lucia, Solari, Dario, Sorensen, Jeffrey, Sorgente, Antonio, Sprugnoli, Rachele, Stranisci, Marco, Tamburini, Fabio, Taylor, Stephen, Tesei, Andrea, Thenmozhi, D., Tonelli, Sara, Torre, Ilaria, Tsakalidis, Adam, Varvara, Rossella, Venturi, Giulia, Vettigli, Giuseppe, Vlad, George-Alexandru, Wang, Benyou, Zaharia, George-Eduard, Zamparelli, Roberto, Zubiaga, Arkaitz
Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::a6b8dc21ad90330097a1a9bc7d4d76bc
http://books.openedition.org/aaccademia/6732
http://books.openedition.org/aaccademia/6732
Stance detection refers to the detection of one’s opinion about the target from their statements. The aim of sardistance task is to classify the Italian tweets into classes of favor, against or no feeling towards the target. The task has two sub-ta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=openedition_::6e9cb3c8e92f3e21ba141cb9937aee52
http://books.openedition.org/aaccademia/7207
http://books.openedition.org/aaccademia/7207
Autor:
R. Rajalakshmi, Chandrabose Aravindan
Publikováno v:
Computational Intelligence. 34:363-396
Web page classification has become a challenging task due to the exponential growth of the World Wide Web. Uniform Resource Locator (URL)-based web page classification systems play an important role, but high accuracy may not be achievable as URL con