Light field (LF) enables high-dimensional image data representation since it can capture spatial and angular information of light rays simultaneously. The low spatial resolution caused by the limited imaging ability of the capturing equipment and the trade-off between spatial and angular resolution greatly affects the quality and application of LF images. In this letter, we propose an end-to-end LF super-resolution (SR) method via geometric feature interaction. Firstly, the low-resolution LF images are stacked in the horizontal and vertical epipolar plane image (EPI) directions and form 3D VI stacks. Then, these stacks are put into a dual-branch network, and we alternately perform 3D convolution on the viewpoint images (VIs) and EPIs by reshaping features for better feature extraction and interaction. The proposed method can fully explore the texture information and geometric consistency of the LF, and super-resolve all VIs at the same time. Experimental results on both real-world and synthetic LF datasets show that the proposed method has higher performance than other state-of-the-art methods.

A compact high-sensitivity probe for sensing up tangential E-field is proposed and measured in this paper. The probe is consisted of an electric dipole with patches used to induce the tangential E-field, a resonator made up of open circuit stubs (capacitor) and short circuit stubs (inductor), for achieving a specific resonance, and a compact coupled balun for transforming the differential- mode voltage into the single output voltage and impedance matching. The probe is fabricated on five-layer dielectric lamina. Compared with the referenced broadband probe, the measured |S12|of the probe is enhanced by 18.81 dB. The proposed probe in this paper is validated with simulation and measurement.

Environmental perception system is the premise of the safety and stability of the autonomous vehicle system. However, studies have shown that the on-board sensors included in the perception system are extremely vulnerable to external attacks and interference, leading to incorrect driving strategies and bringing great security threats. Aiming at the problem, this paper divides the vehicle-mounted sensors into a positioning group and an identification group according to their role in the perception system. Then, based on the information correlation between sensors in the same group and the information correlation of a single sensor on adjacent time series, the distance metric model between sensors in a group and the distance metric model for each sensor of this group on time series is established. And the normal distance intervals corresponding to the confidence interval are calculated respectively. According to the distance metric model between sensors, we can detect anomalies in the perception system in real-time. Further, according to the distance metric model for each sensor on adjacent time series, we can identify anomaly sensors. Our experimental results quantitatively show that the method achieves real-time anomaly recognition, and demonstrate the effectiveness and robustness of the method on the open-source KITTI dataset.

Synaptic crosstalk, which characterizes the interaction between synapses when the neighboring neurons are activated at the same time, plays an important role in the transmission of neural signals. To discover the effect of synaptic crosstalk on associative memory, a memristor-based associative memory circuit considering synaptic crosstalk is proposed in this letter. The inhibitory effect of negative crosstalk on associate memory in the initial learning stage and the consolidation influence of positive crosstalk on associate memory when the synaptic weight exceeds the critical value are revealed. Pspice simulations are conducted on the resultant circuit to verify its correctness.

This study applied the World Health Organization (WHO) guidelines to redesign the Portable Health Clinic (PHC), as a Remote Healthcare System (RHS), for the spread of COVID-19 containment. Additionally, the proposed system not only collects people data but also classifies the case according to the the main symptoms of coronavirus using the COVID-19 triage process (CT-process) based on the analysis of measurement readings taken from patients, where drones are used as a PHC platform and are equipped with the required sensors and essential COVID-19 medications for testing and treating people at their doorstep autonomously when a full curfew is imposed.

Optical and acoustic stereo imaging has great potential for the precise and consistent localization of intervention underwater robots; however, it is still being explored due to its sensing limitations and various technical challenges. This study presents a novel localization method by combining an inertial navigation system and an optical and acoustic stereo imaging system. As a strategy for localization correction relative to underwater structures, the robot’s pose is estimated based on a single acoustic image using a sonar simulator for mid-range localization, and a robust visual tracking using a 3-D wireframe model is employed for high-precision localization near the target structures. The performance of the proposed technique was demonstrated through experimental validation using real data obtained from a test tank.

Utilizing angular-varied illumination in Fourier Ptychography (FP), the resolution of optical microscopes can be increased and the phase of the sample can also be recovered while maintaining a wide field-of-view. In this work, an FP microscopy imaging setup is demonstrated using a 10X 0.28NA objective lens and a dome-shaped LED array illuminator. By increasing the refractive index of the medium between the sample and light sources using oil filled dome, a synthetic system NA of 0.68 is achieved using only 37 LEDs. The measured resolution of 345 nm at a wavelength of 530 nm closely matches the theoretical prediction. Furthermore, the results of the oil-medium illumination are compared to free-space illumination. The oil immersion on the illumination side effectively enhances the illumination NA as compared to air and reduces the need for far off-axis LEDs. The result is high-resolution FP imaging with relatively fewer LEDs providing both short capture and reconstruction times.

Planar antenna arrays of a balanced structure are of great importance in many applications due to their features including low-profile, wideband and high polarisation purity. However, feeding such antennas adds great complexity in terms of manufacturing and reduces the performance due to production of common mode propagation. A method for feeding such antennas using coplanar waveguide on a thin substrate is proposed. Not only does it terminate the antenna of a balanced structure with a single-ended feed but it also enables impedance transformation. The design was an attempt towards a completely printed front-end that incorporates the antenna elements and their feeding circuits on bendable substrates. The electromagnetic performance has been validated with a dual polarized prototype and its prospect for ultrawideband arrays e.g., 5G sub-6 GHz or square kilometre array, was explored.