|
|
|
|
|
Jinghua Groppe, Sven Groppe, Daniel Senf and Ralf Möller
Given a set of software programs, each being labeled either as vulnerable or benign, deep learning technology can be used to automatically build a software vulnerability detector. A challenge in this context is that there are countless equivalent ways to...
ver más
|
|
|
|
|
|
|
|
|
Luana Conte, Emanuele Rizzo, Tiziana Grassi, Francesco Bagordo, Elisabetta De Matteis and Giorgio De Nunzio
Pedigree charts remain essential in oncological genetic counseling for identifying individuals with an increased risk of developing hereditary tumors. However, this valuable data source often remains confined to paper files, going unused. We propose a co...
ver más
|
|
|
|
|
|
|
|
|
Catarina Palma, Artur Ferreira and Mário Figueiredo
The presence of malicious software (malware), for example, in Android applications (apps), has harmful or irreparable consequences to the user and/or the device. Despite the protections app stores provide to avoid malware, it keeps growing in sophisticat...
ver más
|
|
|
|
|
|
|
|
|
Hamed Raoofi, Asa Sabahnia, Daniel Barbeau and Ali Motamedi
Traditional methods of supervision in the construction industry are time-consuming and costly, requiring significant investments in skilled labor. However, with advancements in artificial intelligence, computer vision, and deep learning, these methods ca...
ver más
|
|
|
|
|
|
|
|
|
Miguel A. Borja, Jorge E. Camargo
Pág. 92 - 110
|
|
|
|