1) The document discusses approaches for semantic concept detection in videos using techniques like support vector machines (SVM) and convolutional neural networks (CNN). 2) It proposes a concept detection system that uses SVM and CNN together, extracting features from key frames using Hue moments and classifying the features with SVM and CNN. 3) The outputs of SVM and CNN are fused to improve concept detection accuracy compared to using the classifiers individually. Fusing the two classifiers is intended to better identify the concepts in video frames.