As more and more software projects engage agile methods, there are emerging patterns of
success and failure. With growing adoption of agile methods, project managers increasingly …

Single sample face recognition (SSFR) is a challenging research problem in which only one
face image per person is available for training. Moreover, the face image may have different …

Recently, several machine learning methods for gender classification from frontal facial
images have been proposed. Their variety suggests that there is not a unique or generic …

Faces captured in a real-world scenario may suffer from large variations in shape and
occlusions due to difference in illumination, variation in pose and orientation of a facial …

Quality of facial images has a great impact on the accuracy of the automated face
recognition system. The intraclass variations introduced by varied facial quality due to …

Automated face recognition is commonly used for security reinforcement and identity
verification purposes. While significant advancement has been made in this domain, modern …

Quality of biometric samples has a significant impact on the accuracy of a biometric
recognition system. Various quality factors, such as different lighting conditions, occlusion …

Quality of facial images has a great impact on the accuracy of the automated face
recognition system. Due to the intraclass variations introduced by different facial quality …

Quality assessment of a biometric sample is relatively difficult and understudied problem
compared to the automated recognition and feature extraction in biometrics. More attention …

Recent advances in machine learning research promise to bring us closer to the original
goals of artificial intelligence. Spurred by recent innovations in low-cost, specialized …