High-Resolution Aerial Detection of Marine Plastic Litter by Hyperspectral Sensing

An automatic custom-made procedure is developed to identify macroplastic debris loads in coastal and marine environment, through hyperspectral imaging from unmanned aerial vehicles (UAVs). Results obtained during a remote-sensing field campaign carried out in the seashore of Sassari (Sardinia, Italy) are presented. A push-broom-sensor-based spectral device, carried onboard a DJI Matrice 600 drone, was employed for the acquisition of spectral data in the range 900−1700 nm. The hyperspectral platform was realized by assembling commercial devices, whereas algorithms for mosaicking, post-flight georeferencing, and orthorectification of the acquired images were developed in-house. Generation of the hyperspectral cube was based on mosaicking visible-spectrum images acquired synchronously with the hyperspectral lines, by performing correlation-based registration and applying the same translations, rotations, and scale changes to the hyperspectral data. Plastics detection was based on statistically relevant feature selection and Linear Discriminant Analysis, trained on a manually labeled sample. The results obtained from the inspection of either the beach site or the sea water facing the beach clearly show the successful separate identification of polyethylene (PE) and polyethylene terephthalate (PET) objects through the post-processing data treatment based on the developed classifier algorithm. As a further implementation of the procedure described, direct real-time processing, by an embedded computer carried onboard the drone, permitted the immediate plastics identification (and visual inspection in synchronized images) during the UAV survey, as documented by short video sequences provided in this research paper.

Efficient Memory Organization for DNN Hardware Accelerator Implementation on PSoC

The use of deep learning solutions in different disciplines is increasing and their algorithms are computationally expensive in most cases. For this reason, numerous hardware accelerators have appeared to compute their operations efficiently in parallel, achieving higher performance and lower latency. These algorithms need large amounts of data to feed each of their computing layers, which makes it necessary to efficiently handle the data transfers that feed and collect the information to and from the accelerators. For the implementation of these accelerators, hybrid devices are widely used, which have an embedded computer, where an operating system can be run, and a field-programmable gate array (FPGA), where the accelerator can be deployed. In this work, we present a software API that efficiently organizes the memory, preventing reallocating data from one memory area to another, which improves the native Linux driver with a 85% speed-up and reduces the frame computing time by 28% in a real application.

Design of a Prototype for Vision Prosthesis

This article describes how the field of vision prostheses is currently being developed around the world to restore useful vision for people suffering from retinal degenerative diseases. The vision prosthesis system (VPS) maps visual images to electrical pulses and stimulates the surviving healthy parts in the retina of the eye, i.e. ganglion cells, using electric pulses applied through an electrode array. The retinal neurons send visual information to the brain. This article presents the design of a prototype vision prosthesis system which converts images/video into biphasic electric stimulation pulses for the excitation of electrodes simulated by an LED array. The proposed prototype laboratory model has been developed for the design of flexible high-resolution 1024-electrode VPS, using an embedded computer-based efficient control algorithm for better visual prediction. The prototype design for the VPS is verified visually through a video display on an LCD/LED array. The experimental results of VPS are enumerated for the test objects, such as, palm, human face and large font characters. The results were found to be satisfactory.