Sigmoid and hyperbolic activation functions in long short-term memory (LSTM) and gated
recurrent unit (GRU) based models used in recent studies on video summarization, may …

Video summarization deals with the generation of a condensed version of the original video
by including meaningful frames or segments while eliminating redundant information. The …

The expansion of growth in the generation of video data in various organizations causes an
urgent requirement for effectual video summarization methods. This paper devises a novel …

There has been a vast augmentation in quantity of Video Content (VC) generated amid the
last some years. The Video Summarization (VS) approach is introduced for managing the …

Image saliency is determined by spatial semantic features, while video saliency is affected
by multiple factors such as spatial and temporal information. Since human eyes stay …

Human eye movements indicate important spatial information in static images and videos.
However, videos contain additional temporal information and convey a storyline. We explore …

Video summarization is an ideal tool for skimming videos. Previous computational models
extract explicit information from the input video, such as visual appearance, motion or audio …

From the earliest experiments with artificial neurons to the development of convolutional
neural networks and beyond, nature has proven to be an inexhaustible source of inspiration …

The conventional interpretation of sports events is a radical task argued over the past
decades [137]. Event detection is emphasized as essential to process and analyze the …

Video summarization is the process of making summary of a video by extracting the key
frames. Our content based video summarization approach is based on birds foraging search …