We propose a novel architecture called the Multi-view Self-Constructing Graph Convolutional Networks (MSCG-Net) for semantic segmentation. Building on the recently proposed Self-Constructing Graph (SCG) module, which makes use of learnable latent variables to self-construct the underlying graphs directly from the input features without relying on manually built prior knowledge graphs, we leverage ...

Due to its great creative potential for innovation and scientific discovery, inter- and multidisciplinary collaboration is being increasingly encouraged by institutions and funding agencies. The increased opportunities in the multidisciplinary arena also come with significant challenges like the added experimental, analytical and logistical complexity, blended with a high likelihood of miscommunications. ...

Multifocus microscopy enables recording of entire volumes in a single camera exposure. In dense samples, multifocus microscopy is severely hampered by background haze. Here, we introduce a scalable multifocus method that incorporates optical sectioning and offers axial superresolution capabilities. In our method, a dithered oblique light-sheet scans the sample volume during a single exposure, while ...

Visualization of three-dimensional (3D) morphological changes in the subcellular structures of a biological specimen is a major challenge in life science. Here, we present an integrated chip-based optical nanoscopy combined with quantitative phase microscopy (QPM) to obtain 3D morphology of liver sinusoidal endothelial cells (LSEC). LSEC have unique morphology with small nanopores (50-300 nm in ...

Lead Zirconate Titanate (PZT) is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several micro-defects develop in the PZT sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is thus necessary to identify, locate, and quantify the defects. Non-Destructive Structural Health Monitoring ...

A recurrent neural network (RNN) is a universal approximator of dynamical systems, whose performance often depends on sensitive hyperparameters. Tuning them properly may be difficult and, typically, based on a trial-and-error approach. In this work, we adopt a graph-based framework to interpret and characterize internal dynamics of a class of RNNs called echo state networks (ESNs). We design principled ...

The performance of piezoelectric sensors deteriorated due to the presence of defect, delamination, and corrosion that needed to be diagnosed for the effective implementation of the structural health monitoring (SHM) framework. A novel experimental approach based on Coulomb coupling is devised to visualise the interaction of ultrasonic waves with microscale defects in the Lead Zirconate Titanate (PZT). ...

In this paper, we present the experimental setup and data collection during the Norwegian Radar oil Spill Experiment 2015, followed by a comparison of a subset of the multisensory synthetic aperture radar (SAR) imagery collected during the experiment. Multipolarization SAR data acquired by Radarsat-2, TerraSAR-X, and the uninhabited aerial vehicle synthetic aperture radar (UAVSAR) less than 6 min ...

A statistical model for multilook polarimetric radar data is presented where the polarimetric channels are associated with individual texture variables having potentially different statistical properties. The feasibility of producing closed form probability density functions under certain restrictions is outlined. Mellin kind statistics are derived under various assumptions on the texture variables, ...

We present an open-source implementation of the fluctuation-based nanoscopy method MUSICAL for ImageJ. This implementation improves the algorithm’s computational efficiency and takes advantage of multi-threading to provide orders of magnitude faster reconstructions than the original MATLAB implementation. In addition, the plugin is capable of generating super-resolution videos from large stacks of ...