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Audio event detection aims at discovering the elements inside an audio clip. In addition to labeling the clips with the audio events, we want to find out the temporal locations of these events. However, creating clearly annotated training data can be time-consuming. Therefore, we provide a model based on convolutional neural networks that relies only on weakly-supervised data for training. These data...
Based on Gibbs sampling technology, this paper puts forward a new semi-blind joint channel estimation and equalization algorithm that used in signal carrier coherent underwater acoustic communication system. First of all, we estimate the channel by using the train sequence with a loop structure before the data, and according to the sparse characteristics of underwater acoustic channel, this paper...
Knowledge management system of flight safety and efficiency is very important for air traffic control staffs and drivers; and individuals with related knowledge is the main resource of the knowledge database. ATC staffs' abilities and techniques are key elements to avoid errors. This research, we design and build the course exams based on ADDIE model and SCORM (Sharable Content Object Reference Model)...
Face detection is widely used in portable consumer handheld devices aimed at low area, low power, and high performance applications. The boosted cascade algorithm is one of the fastest face detection algorithms in use, but its hardware implementation requires a huge amount of SRAM to store the input data, integral image, and classifiers. This paper proposes a novel cascade face detection architecture...
In this paper, we present a novel face detection architecture based on the boosted cascade algorithm. A reduced two-field feature extraction scheme for integral image calculation is proposed. Based on this scheme, the required memory for storing integral images is reduced from 400 Kbits to 2.016 Kbits for a 160??120 gray scale image. The range of the feature size and location is also reduced so the...
This paper proposes the use of genetic algorithm to select an optimal feature set for distinguishing computer graphics from digital photographic images. Our previously developed approach has derived a 234-D feature vector from each test image in HSV color space. The statistical moments of characteristic functions of the image and its wavelet subbands were selected as the distinguishing image features...
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