Binary code fingerprinting is crucial in many security applications. Examples include
malware detection, software infringement, vulnerability analysis, and digital forensics. It is …

Benchmark datasets are critical for develo**, evaluating, and comparing remote sensing
image retrieval (RSIR) approaches. However, current benchmark datasets are deficient in …

Abstract The region-based Convolutional Neural Network (CNN) detectors such as Faster R-
CNN or R-FCN have already shown promising results for object detection by combining the …

Biometric recognition, or simply biometrics, refers to the use of distinctive anatomical and/or
behavioral characteristics or identifiers (eg, fingerprints, face, iris, voice, and hand geometry) …

Abstract Objects and their relationships are critical contents for image understanding. A
scene graph provides a structured description that captures these properties of an image …

The field of object detection has made great progress in recent years. Most of these
improvements are derived from using a more sophisticated convolutional neural network …

Latent fingerprint identification is of critical importance to law enforcement agencies in
identifying suspects: Latent fingerprints are inadvertent impressions left by fingers on …

Fingerprint recognition has found a reliable application for verification or identification of
people in biometrics. Globally, fingerprints can be viewed as valuable traits due to several …

In this work, we propose a novel latent fingerprint enhancement method based on FingerNet
inspired by recent development of Convolutional Neural Network (CNN). Although CNN is …

Identifying latent fingerprints is of vital importance for law enforcement agencies to
apprehend criminals and terrorists. Compared to live-scan and inked fingerprints, the image …