Incremental learning refers to learning from streaming data, which arrive over time, with
limited memory resources and, ideally, without sacrificing model accuracy. This setting fits …

Deep neural network (DNN) has been used as a learning model for modeling the
hierarchical architecture of human brain. However, DNN suffers from problems of learning …

Accurate fruit classification is difficult to accomplish because of the similarities among the
various categories. In this paper, we proposed a novel fruit‐classification system, with the …

Face recognition (FR) plays an important role in video surveillance by allowing to accurately
recognize individuals of interest over a distributed network of cameras. Systems for still-to …

Personalized movie summarization is demand of the current era due to an exponential
growth in movies production. The employed methods for movies summarization fail to satisfy …

In video surveillance, face recognition (FR) systems are employed to detect individuals of
interest appearing over a distributed network of cameras. The performance of still-to-video …

Face recognition (FR) systems for video surveillance (VS) applications attempt to accurately
detect the presence of target individuals over a distributed network of cameras. In video …

Most myoelectric prosthetic hands use a fixed pattern recognition model to identify the user's
hand motion commands. Since surface electromyogram (sEMG) characteristics vary with …

This paper presents an ensemble face recognition system which makes use of the novel
local descriptor called Dense Local Graph Structure (D-LGS) which is exploited from …

Sparse representation-based classification (SRC) has been shown to achieve a high level of
accuracy in face recognition (FR). However, matching faces captured in unconstrained video …