scholarly journals Real-Time Object Detection for Aiding Visually Impaired using Deep Learning

2020 ◽  
Vol 9 (4) ◽  
pp. 1600-1605 ◽  
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Internet Of Things ◽  
Computer Science ◽  
Visually Impaired ◽  
Vision Loss ◽  
Assistive Device ◽  
Blind People ◽  
Normal People ◽  
The People

This research aims to create an assistive device for the people who are suffering from vision loss or impairment. The device is designed for blind people to overcome the daily challenges they face which may be perceived to be trivial to normal people. The device is created by using advance computer science technologies such as deep learning, computer vision and internet of things. The device created would be able to detect and classify daily objects and give a voice feedback to the user who is handicapped with blindness.

Reading Assistance for Visually Impaired People Using TTL Serial Camera With Voice

2018 ◽  
pp. 170-180
Author(s):  
Sruthi M. ◽  
Rajasekaran R.
Keyword(s):  
Internet Of Things ◽  
Visually Impaired ◽  
People With Disabilities ◽  
The Internet ◽  
Blind People ◽  
Text Book ◽  
Visually Impaired People ◽  
Impaired People

Internet of things is where all the things are connected to the internet and communicate with each other. There are many applications of the IoT in various fields such as healthcare, agriculture, industries, and logistics, and even for empowering people with disabilities. There are many previous work for the blind people using IoT in finding the obstacles many navigation applications have been developed. In this chapter, a system is proposed to assist blind people in reading books. This method is based on capturing the text book pages as an image and processing them into text with speech as an output.

scholarly journals A deep learning platooning-based video information-sharing Internet of Things framework for autonomous driving systems

2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988313 ◽  
Author(s):  
Zishuo Zhou ◽  
Zahid Akhtar ◽  
Ka Lok Man ◽  
Kamran Siddique
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Deep Learning ◽  
Internet Of Things ◽  
Information Sharing ◽  
Communication Technology ◽  
Empirical Evaluation ◽  
Traffic Lights ◽  
Video Information ◽  
Safety And Stability

To enhance the safety and stability of autonomous vehicles, we present a deep learning platooning-based video information-sharing Internet of Things framework in this study. The proposed Internet of Things framework incorporates concepts and mechanisms from several domains of computer science, such as computer vision, artificial intelligence, sensor technology, and communication technology. The information captured by camera, such as road edges, traffic lights, and zebra lines, is highlighted using computer vision. The semantics of highlighted information is recognized by artificial intelligence. Sensors provide information on the direction and distance of obstacles, as well as their speed and moving direction. The communication technology is applied to share the information among the vehicles. Since vehicles have high probability to encounter accidents in congested locations, the proposed system enables vehicles to perform self-positioning with other vehicles in a certain range to reinforce their safety and stability. The empirical evaluation shows the viability and efficacy of the proposed system in such situations. Moreover, the collision time is decreased considerably compared with that when using traditional systems.

scholarly journals Deep learning approaches to pattern extraction and recognition in paintings and drawings: an overview

2021 ◽  
Author(s):  
Giovanna Castellano ◽  
Gennaro Vessio
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Computer Science ◽  
Visual Arts ◽  
Visual Art ◽  
Learning Approaches ◽  
Pattern Extraction ◽  
Art Collections ◽  
Recent Advances ◽  
Art Community

AbstractThis paper provides an overview of some of the most relevant deep learning approaches to pattern extraction and recognition in visual arts, particularly painting and drawing. Recent advances in deep learning and computer vision, coupled with the growing availability of large digitized visual art collections, have opened new opportunities for computer science researchers to assist the art community with automatic tools to analyse and further understand visual arts. Among other benefits, a deeper understanding of visual arts has the potential to make them more accessible to a wider population, ultimately supporting the spread of culture.

scholarly journals Indoor Navigation Systems for Blind People

2018 ◽  
Author(s):  
Ali Hojjat
Keyword(s):  
Computer Vision ◽  
Visually Impaired ◽  
Indoor Navigation ◽  
Blind People ◽  
Navigation Systems ◽  
Visually Impaired People ◽  
Impaired People ◽  
Outdoor Environments

Indoor navigation systems must deal with absence of GPS signals, since they are only available in outdoor environments. Therefore, indoor systems have to rely upon other techniques for positioning users. Recently various indoor navigation systems have been designed and developed to help visually impaired people. In this paper an overview of some existing indoor navigation systems for visually impaired people are presented and they are compared from different perspectives. The evaluated techniques are ultrasonic systems, RFID-based solutions, computer vision aided navigation systems, ans smartphone-based applications.

scholarly journals A survey on computer vision technology in Camera Based ETA devices

2015 ◽  
Vol 1 (3) ◽  
pp. 115
Author(s):  
Amir Ramezani Dooraki
Keyword(s):  
Computer Vision ◽  
Object Recognition ◽  
Computer Science ◽  
Stereo Vision ◽  
Visually Impaired ◽  
High Potential ◽  
Methods And Techniques ◽  
Computer Vision Technology ◽  
Visually Impaired Persons ◽  
Vision Technique

Electronic Travel Aid systems are expected to make impaired persons able to perform their everyday tasks such as finding an object and avoiding obstacles easier. Among ETA devices, Camera Based ETA devices are the new one and with a high potential for helping Visually Impaired Persons. With recent advances in computer science and specially computer vision, Camera Based ETA devices used several computer vision algorithms and techniques such as object recognition and stereo vision in order to help VIP to perform tasks such as reading banknotes, recognizing people and avoiding obstacles. This paper analyses and appraises a number of literatures in this area with focus on stereo vision technique. Finally, after discussing about the methods and techniques used in different literatures, it is concluded that the stereo vision is the best technique for helping VIP in their everyday navigation.

Artificial Intelligence and Machine Learning Algorithms

2020 ◽  
pp. 188-219
Author(s):  
Amit Kumar Tyagi ◽  
Poonam Chahal
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Big Data ◽  
Deep Learning ◽  
Internet Of Things ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Learning Techniques

With the recent development in technologies and integration of millions of internet of things devices, a lot of data is being generated every day (known as Big Data). This is required to improve the growth of several organizations or in applications like e-healthcare, etc. Also, we are entering into an era of smart world, where robotics is going to take place in most of the applications (to solve the world's problems). Implementing robotics in applications like medical, automobile, etc. is an aim/goal of computer vision. Computer vision (CV) is fulfilled by several components like artificial intelligence (AI), machine learning (ML), and deep learning (DL). Here, machine learning and deep learning techniques/algorithms are used to analyze Big Data. Today's various organizations like Google, Facebook, etc. are using ML techniques to search particular data or recommend any post. Hence, the requirement of a computer vision is fulfilled through these three terms: AI, ML, and DL.

Comparative Analysis of Intelligent Driving and Safety Assistance Systems Using YOLO and SSD Model of Deep Learning

2021 ◽  
Vol 12 (1) ◽  
pp. 131-146
Author(s):  
Nidhi Sindhwani ◽  
Shekhar Verma ◽  
Tushar Bajaj ◽  
Rohit Anand
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Deep Learning ◽  
Comparative Analysis ◽  
Internet Of Things ◽  
Road Accidents ◽  
The Road ◽  
The World ◽  
Assistance Systems ◽  
On The Road

Bad road conditions are one of the main causes of road accidents around the world. These kinds of accidents prove to be fatal as many lives are lost in these accidents that are mainly caused by potholes or distress on surface of roads. This paper suggests a system that will not only help in reducing the chances of these accidents by making the driver aware of the upcoming distress/potholes on the road but also saving the location of these potholes which can be sent to respective authorities so that they can be repaired. The authors have used technologies like image processing, computer vision, deep learning, and internet of things (IoT) to make this happen. It uses a camera mounted in front near windshield that will capture the images which will be further be processed to get the location of the potholes and distress on road. These detected potholes can be projected on a heads-up display (HUD) placed near windshield which will notify the driver of the potholes.

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