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Convolutional neural network (CNN) has become a successful algorithm in the region of artificial intelligence and a strong candidate for many computer vision algorithms. But the computation complexity of CNN is much higher than traditional algorithms. With the help of GPU acceleration, CNN-based applications are widely deployed in servers. However, for embedded platforms, CNN-based solutions are still...
Real-time pedestrian detection and tracking are vital to many applications, such as the interaction between drones and human. However, the high complexity of Convolutional Neural Network (CNN) makes them rely on powerful servers, thus is hard for mobile platforms like drones. In this paper, we propose a CNN-based real-time pedestrian detection and tracking system, which can achieve 14.7 fps detection...
Online anomaly detection (AD) is an important technique for monitoring wireless sensor networks (WSNs), which protects WSNs from cyberattacks and random faults. As a scalable and parameter-free unsupervised AD technique, $(k)$-nearest neighbor (kNN) algorithm has attracted a lot of attention for its applications in computer networks and WSNs. However, the nature of lazy-learning makes the kNN-based...
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