Results 91 to 100 of about 26,776 (176)

Learning Geometry Information of Target for Visual Object Tracking with Siamese Networks. [PDF]

Sensors (Basel), 2021
Chen H, Zhang W, Yan D.
europepmc   +1 more source

Siamese-Derived Attention Dense Network for Seismic Impedance Inversion

Mathematics
Seismic impedance inversion is essential for providing high-resolution stratigraphic analysis. Therefore, improving the accuracy while ensuring the efficiency of the inversion model is crucial for practical implementation.
Jiang Wu
doaj   +1 more source

Experiments of Image Classification Using Dissimilarity Spaces Built with Siamese Networks. [PDF]

Sensors (Basel), 2021
Nanni L, Minchio G, Brahnam S, Maguolo G, Lumini A.   +4 more
europepmc   +1 more source

AISMSNet: Advanced Image Splicing Manipulation Identification Based on Siamese Networks

Applied Sciences
The exponential surge in specialized image editing software has intensified visual forgery, with splicing attacks emerging as a popular forgery technique.
Ana Elena Ramirez-Rodriguez, Rodrigo Eduardo Arevalo-Ancona, Hector Perez-Meana, Manuel Cedillo-Hernandez, Mariko Nakano-Miyatake   +4 more
doaj   +1 more source

Closing the Performance Gap between Siamese Networks for Dissimilarity Image Classification and Convolutional Neural Networks. [PDF]

Sensors (Basel), 2021
Nanni L, Minchio G, Brahnam S, Sarraggiotto D, Lumini A.   +4 more
europepmc   +1 more source

DSN-STC: Leveraging Siamese networks for optimized short text clustering. [PDF]

PLoS One
Molaei M, Feizi-Derakhshi MR, Balafar MA, Tanha J.   +3 more
europepmc   +1 more source

Application of Siamese Networks to the Recognition of the Drill Wear State Based on Images of Drilled Holes. [PDF]

Sensors (Basel), 2020
Kurek J, Antoniuk I, Świderski B, Jegorowa A, Bukowski M.   +4 more
europepmc   +1 more source

Contactless biometric verification from in-air signatures using deep siamese networks. [PDF]

Sci Rep
Salturk S, Pamukcu TE, Kahraman N.
europepmc   +1 more source

Multi-Object Tracking Algorithm for RGB-D Images Based on Asymmetric Dual Siamese Networks. [PDF]

Sensors (Basel), 2020
Zhang WL, Yang K, Xin YT, Zhao TS.
europepmc   +1 more source

Siamese networks for generating adversarial examples

, 2018
Machine learning models are vulnerable to adversarial examples. An adversary modifies the input data such that humans still assign the same label, however, machine learning models misclassify it. Previous approaches in the literature demonstrated that adversarial examples can even be generated for the remotely hosted model.
Kulkarni, Mandar, Abubakar, Aria
openaire   +1 more source