ADVANCING VIDEO SEARCH CAPABILITIES: INTEGRATING FEEDFORWARD NEURAL NETWORKS FOR EFFICIENT FRAGMENT-BASED RETRIEVAL
In the context of rapidly increasing volumes of video data, the problem of their efficient search and analysis becomes more acute. This research aims to develop and test an innovative system to improve the speed and accuracy of video search, utilizing the capabilities of Deep Convolutional Neural Networks (DCNN) and Feedforward Neural Networks (FFNN).