Abstract: Convolutional neural networks (CNNs) have attracted much attention in change detection (CD) for their superior feature learning ability. However, most of the existing CNN-based CD methods ...
Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
Abstract: Although the vision transformer-based methods (ViTs) exhibit an excellent performance than convolutional neural networks (CNNs) for image recognition tasks, their pixel-level semantic ...
Abstract: Sequential recommender systems seek to capture information about user affinities and behaviors considering their sequential series of interactions. While former models based on Markov Chains ...
Abstract: Light detection and ranging (LiDAR) point cloud denoising is critical for reliable environmental perception in autonomous driving and robotics. To overcome the lack of real-noise datasets ...
Abstract: This paper proposes a method to improve the accuracy of an absolute magnetic encoder by using harmonic rejection (HR) and a dual-phase-locked loop (DPLL). The encoder consists of two ...
Abstract: Power quality issues are required to be addressed properly in forthcoming era of smart meters, smart grids and increase in renewable energy integration. In this paper, Deep Auto-encoder (DAE ...
Abstract: This brief presents a power and memory-optimized hardware implementation for the open forward error correction (oFEC) encoder proposed for high-speed fiber ...
Abstract: The promotion of the HEVC standard has significantly alleviated the burden of network transmission and video storage. However, its inherent complexity and data dependencies pose a ...
Abstract: Unsupervised anomaly detection (UAD) aims to recognize anomalous images based on the training set that contains only normal images. In medical image analysis, UAD benefits from leveraging ...
Abstract: Precise measurement of the rotor speed is mandatory for machine tool spindle drives and other drives having the same demands for the accuracy of speed stabilization. These drives commonly ...
Abstract: Transformers are widely used in natural language processing and computer vision, and Bidirectional Encoder Representations from Transformers (BERT) is one of the most popular pre-trained ...