The handwritten string recognition is still a challengeable task, though the powerful deep learning tools were introduced. In this paper, based on TAO-FCN, we proposed an end-to-end system for handwritten string recognition. Compared with the conventional methods, there is no preprocess nor manually designed rules employed. With enough labelled data, it is easy to apply the proposed method to d...

Recent approaches for instance-aware semantic labeling have augmented convolutional neural networks (CNNs) with complex multitask architectures or computationally expensive graphical models. We present a method that leverages a fully convolutional network (FCN) to predict semantic labels, depth and an instance-based encoding using each pixel’s direction towards its corresponding instance center...

Gait trajectory prediction models have several applications in exoskeleton control; they can be used as feed-forward input to low-level controllers and generate reference/target trajectories for position-controlled exoskeletons. In our study, we implement four deep learning (LSTM, FCN, CNN Transformer) that perform one-step-ahead gait after training on patterns of typically developing children....

The retina is one of the most developed sensing organs in human body. However, knowledge on coding and decoding retinal neurons are still rather limited. Compared with (i.e., transforming visual scenes to spike trains), reconstructing from trains, especially those complex stimuli) more receives less attention. In this paper, we focus accurate reconstruction their trains by designing a train dec...

Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As variant of the Convolutional Neural Network (CNN), Fully (FCN), designed for pixel-to-pixel tasks, obtained enormous success semantic segmentation. Therefore, effectively using FCN model combined with polarimetric characteristics PolSAR quite pro...

Spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) is a new remote sensing technology that uses GNSS signals reflected from the Earth’s surface to estimate geophysical parameters. Because of its unique advantages such as high temporal and spatial resolutions, low observation cost, wide coverage all-weather operation, it has been widely used in land ocean fields. Ocean wind mon...

State-of-the-art presentation attack detection approaches tend to overfit the instruments seen during training and fail generalize unknown instruments. Given that face is inherently a local task, we propose framework, namely Self-Supervised Regional Fully Convolutional Network (SSR-FCN), trained learn discriminative cues from image in self-supervised manner. The proposed framework (i) improves ...

SD-OCT is a non invasive cross sectional imaging modality useful for diagnosis of macular defects. Efficient detection and segmentation of the abnormalities seen as biomarkers in OCT can help in analyzing the progression of the disease and advising effective treatment for the associated disease. In this work we proposes a fully automated Generalized Motion Pattern(GMP) based segmentation method...