(National University of Kyiv)
📅Oct 04, 2019
In our work we will study the possibility of replacing monolithic ADC with a combination of Comparator and DAC. Adding FPGA resources (memory, hardware multipliers, configurable logic, etc.) to the Comparator+DAC structure will allow us to obtain flexible data acquisition system for various applications.
We plan to use this technology to create Time-domain reflectometer (TDR) and Sampling Oscilloscope with an equivalent sampling rate of up to 3 GS/s.
📁High Performance Computing
(Ain Shams University)
📅Oct 15, 2019
Many regions, all over the world nowadays, are suffering severely from several contemporary issues that without a doubt are hindering the overall world progressions toward reaching a more prosperous economic status. Moreover, most of these issues are related directly to the failure of monitoring the borders thoroughly.
The main goal of this project is to propose an appropriate Artificial Intelligence (AI) based solution that could substantially increase the efficiency of border monitoring by creating a wireless network using ultra-low power nodes that could capable to detect any suspicious intruding behaviors. The design of the proposed project depends on three main stages: The sensory data fusion interface; The biological inspired Fuzzy Logic (FL) system controller; and the Wireless Sensor Network (WSN) interface stage.
(University of Applied Sciences Darmstadt)
📅Aug 29, 2019
For many visually disabled people it is challenging to identify other persons and classify objects correctly. A wearable infrared camera system with multiple, real-time convolutional neural network would be helpful for low vision affected and increases the confidence in rain, fog and darkness.
We would like to compare two established technology approaches and unite the individual advantages of the 110,000 reconfigurable logic elements and the sequential ARM Cortex-A9 hardcore processor on the Terasic DE10-Nano SoC.
Our project objective is a small, helpful bodycam for 217,000,000 visually handicapped people!
Index Terms: Field programmable gate arrays, Neural network hardware, Fixed-point arithmetic, 2D convolution
📅Jun 15, 2019
This project will be developed for Rhumel SA, a small european fintech company aiming at assisting decision making in finance.
Throughout the last eleven years since the '08 crisis, the industry has been relying heavily on standard algorithmic approach as well as low interest rate for its development. But those two approaches have their limits.
Although the latter has helped to provide an apparent sluggish recovery, non conventional economic stimuli can't last forever as they tend to create bubbles. As for the algorithmic approach (HFT,indexes), the flash crash of 2010 has proven that under particular conditions, this technology hasn't helped improving market liquidity when most needed, quite the opposite. An average of 90% of trades placed by machines are canceled ...
Machine learning on the other hand, could help processing charts (graphic chart analysis on particular companies going back to the '70s) and help active investors process the information that really matters.
The intent of that project, would be to use the openVINO starter kit to implement a Convolution Neural Network (CNN) for candle stick charts (Open High Low Close or more commonly OHLC).
1) Machine learning for chart analysis:
First focusing on one company, say Intel for example, and going back to its introduction in the market, openVINO could be used to graphically analysis on candle stick charts and give sensible insight in other it is a good idea or not to invest in the stock. This very long term approach is radically different from what exist at the moment in the market.
2) OpenVINO and the state of the art:
Intel website already provides examples and articles concerning dealing with CNN. The idea here is to start from those examples (Alex Net image classification, the R-CNN demo) and implement a sequence of Convolution filter and Pooling filters in order to replicate the human chart analysis but on a much bigger scale.
The final aim of Rhumel is to help money flowing back to the real economy using modern tools and being pragmatic.
Thus, contributing in financing small businesses, avoiding bubbles, keeping governments and institutions out of debt.
In other words, contributing to have a sound economy again.
📁Internet of Things
(University ABOU BEKR BELKAID of Tlemcen)
📅Oct 06, 2019
Currently, it is not possible to live without electricity. Our lifestyles influence this resource consumption. Indeed, it is obvious that each one of us with his own attitude and mores imposes a certain profile to electrical consumption. This project aims to develop a solution that allows smart remote measurements of electricity consumption. Artificial intelligence (AI) is used to properly analyze the consumption profile targeting individuals identification who certainly have different lifestyles. Moreover, adequate intelligence applied to consumption measurements makes it possible to guess the type of machines used. We also aim to associate with the developed system intelligence, Home automation control planning the residents' actions.
(Universitat Autonoma de Barcelona)
📅Oct 06, 2019
Collecting Mushrooms for human consumption is a very popular activity in Catalonia. It is so popular that the goverment is often discussing methods to control access to the forests of the country, including tolls. There are hundreds of different mushroom especies, some are very appreciated, and some are poisonous, and even can cause death. There are a number of fatalities every day because of mushroom intoxication.
The exact identification of mushroom especies is an important challenge that can save lives. The aim of this project is to build a machine learning system to identify each mushroom especies from photos taken with mobile phones.
(university of Guilan)
📅Oct 08, 2019
Todays, because of importance of performance, efficiency, cost and product presentation time, the influence of artificial intelligence (AI) in smart manufacturing is rapidly growing. Thus, we attempt to present a new type of smart glasses for the blind people by using AI with machine learning to improve their quality of life. In fact, our proposal can help visually-impaired people, specifically, completely blind people to identify person, detect objects, cross the street and generally, help them to navigate and find orientation without any assistance.
Our smart assistive device is very high efficient because of using FPGA implementation. In this system, we use a DE10-Nano SoC FPGA kit and a camera as main hardware. Also, we use an audio system and other software/hardware peripherals to complete the requirements of the target device.
📅Jul 18, 2019
Introduction: Each year an enormous number of people die from skin diseases.
Based on BSD Work Group and the American Academy of Dermatology (AAD) there is 85 million US patient were diagnosed with at least one skin disease in 2013 (25% of the US population).
According to a study in 2016 from the “French society of dermatology” 16 million French suffer from a skin disease, and 80% of those suffer from more than 1 pathology which makes 24% of the French population.
Referring to the article “The burden of skin disease in the United States” in the journal of the AAD, 24 different categories of skin pathologies can be identified each one including at least 4 diseases.
Problematic: Using this approximation, there is a minimum of 100 diseases. With this huge number of diseases, it implies prognostic more difficult to establish for doctors. Furthermore, patients who have these types of disease, they feel shy. Furthermore, patients who have these types of disease, they feel shy. As well as, psychological problems and stress.
📁Internet of Things
(Poznan University of Technology)
📅Oct 06, 2019
In the era of constantly growing traffic we are challenged to find the best solutions not only for car movement organization but also for adequate parked car management. Therefore, we have to develop bigger and more complicated parking spaces than ever before. Facing these infrastructures can be tricky for many drivers and they can feel overwhelmed by car parks complexity. Innovative IoT solutions come to help these drivers who are straying in the darkness of underground car parks.
ParkMe is a simple idea for managing car park traffic based on video processing, routing, guiding and tracking of free parking places. ParkMe’s main functionality is to guide every single car individually from the car park’s entrance to a park place most suitable to driver’s needs and then all the way back to the least occupied exit.
We value the time above everything else. ParkMe is a time-saving solution for all complex parking infrastructures. With our project we would like to put an end to: - crawling around a parking & searching for a parking place, - traffic jams in the parking areas, - that irritating feeling when someone takes a place that you just spotted. Our solution will save a lot of driver’s time, which can be spent on doing something more constructive than being stuck in a traffic jam.
ParkMe’s infrastructure is based on sophisticated nodes called GuideNests, which contain Terasic FPGA boards with Intel OpenVINO Toolkit for image processing, sensors, indicators and connectivity with central server and other existing systems. GuideNests let the system individually identify every car in the car park. With the support of traffic monitoring and free parking places indicators the system can calculate the route for every driver, considering changeable environment of the car park. The system is scalable and can be expanded due to specific implementation case.
With enough time a human being is capable to do anything. Don’t waste it for parking traffic!
📁High Performance Computing
(Xavier University - Ateneo de Cagayan)
📅Oct 07, 2019
In photography, aperture is the opening within the lens through which light travels. It determines the cone angle of light from the image plane. One of the effects of aperture is depth of field. Depth of field is the amount of your photograph that appears sharp from front to back. The further an object from the focus plane, the more blurry it appears in the photo. Conversely, if we can find a way to measure sharpness of an object through digital image processing, we can determine the relative distance of all the objects in an image and even surfaces. With the computing ability of FPGA, it can easily produce an elevation map of an area which can be used for better image analysis, urban planning, and disaster risk assessment.
📁Internet of Things
(National Research University Higher School of Economics)
📅Oct 07, 2019
Purpose: to create a 3D printer that helps to prevent failures and problems during a printing progress, to have a user-friendly control interface (LCD display), an isolated body and a large printing area.
Applications: The scope of 3D printers application is wide. We use SoC to provide functioning of the printer with advanced features. SoC is used to generate signals for the mechanical parts of the printer, to realize high-level information processing algorithms, and to provide the interaction interface to users.
Target user: This product is a prototype of future 3D printers on SoC. At present, there are no similar products in the middle price segment. Our team presents a new concept of a printer control system which provides a convenient user interface with the possibility of further connection to smart home systems using IoT technology.
📅Oct 08, 2019
The aim of our project is to develop the real-time video frame depth reconstruction device using FPGA.
There are a lot of classical algorithms of depth map reconstructing, but even the finest of them do it slowly, it takes a few seconds to process even a single frame.
These approaches don’t work in real-time.
Within the project, we are intended to develop the device, which can speed up a frame depth map reconstruction process, dealing with that task in real time without reduction in the processing result quality.
To construct a real-time depth map we use a special architecture deep neural network, implemented in FPGA, which processes two images from stereo-pare simultaneously.
FPGA enables the user to make this process more efficient than CPU thanks to implementation of both the parallel architecture and pipelines, so we achieve a great speed up of this process with help of parallel data processing and pipelining in data flow.