Lianwen Jin

TL;DR: A multi-object rectified attention network (MORAN) for general scene text recognition that can read both regular and irregular scene text and achieves state-of-the-art performance.

TL;DR: A high-accuracy human activity recognition system based on single tri-axis accelerometer for use in a naturalistic environment that exploits the discrete cosine transform, the Principal Component Analysis (PCA) and Support Vector Machine for classification human different activity.

TL;DR: A CNN-based MD-YOLO framework for multi-directional car license plate detection that can elegantly manage rotational problems in real-time scenarios and outperforms over other existing state-of-the-art methods in terms of better accuracy and lower computational cost.

TL;DR: Wang et al. as discussed by the authors proposed a new CNN based method, named Deep Matching Prior Network (DMPNet), to detect text with tighter quadrangle, which uses quadrilateral sliding windows in several specific intermediate convolutional layers to roughly recall the text with higher overlapping area and then a shared Monte-Carlo method is proposed for fast and accurate computing of the polygonal areas.

TL;DR: A new Convolutional Neural Networks (CNNs) based method, named Deep Matching Prior Network (DMPNet), to detect text with tighter quadrangle, which has better overall performance than L2 loss and smooth L1 loss in terms of robustness and stability.