Machine Intelligence to Assist Visually Impaired People: A Big Data Deep Neural Network Adventure

2018 ◽  
Author(s):  
Fereshteh S. Bashiri ◽  
Eric Larose ◽  
Jonathan Badger ◽  
Zeyun Yu ◽  
Peggy Peissig ◽  
...  
Keyword(s):  
Neural Network ◽  
Big Data ◽  
Visually Impaired ◽  
Deep Neural Network ◽  
Machine Intelligence ◽  
Visually Impaired People ◽  
Impaired People

Object Detection to Assist Visually Impaired People: A Deep Neural Network Adventure

2018 ◽  
pp. 500-510 ◽  
Author(s):  
Fereshteh S. Bashiri ◽  
Eric LaRose ◽  
Jonathan C. Badger ◽  
Roshan M. D’Souza ◽  
Zeyun Yu ◽  
...  
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Visually Impaired ◽  
Deep Neural Network ◽  
Visually Impaired People ◽  
Impaired People

scholarly journals Real-Time Object Detection using Deep Learning and Open CV

2019 ◽  
Vol 8 (12S) ◽  
pp. 411-414
Keyword(s):  
Neural Network ◽  
Object Detection ◽  
Visually Impaired ◽  
Deep Neural Network ◽  
Raspberry Pi ◽  
Detailed Review ◽  
Real World Application ◽  
Satisfactory Performance ◽  
Visually Impaired People ◽  
Impaired People

The object detection is used in almost every realworld application such as autonomous traversal, visual system, face detection and even more. This paper aims at applying object detection technique to assist visually impaired people. It helps visually impaired people to know about the objects around them to enable them to walk free. A prototype has been implemented on a Raspberry PI 3 using OpenCV libraries, and satisfactory performance is achieved. In this paper, detailed review has been carried out on object detection using region – conventionaal neural network (RCNN) based learning systems for a real-world application. This paper explores the various process of detecting objects using various object detections methods and walks through detection including a deep neural network for SSD implemented using Caffe model.

scholarly journals Object Detection and Recognition for Visually Impaired People

2020 ◽  
Vol 9 (4) ◽  
pp. 401-405
Keyword(s):  
Neural Network ◽  
Visually Impaired ◽  
Deep Neural Network ◽  
Sufficient Information ◽  
Blind People ◽  
The Real ◽  
Visually Impaired People ◽  
Impaired People ◽  
Familiar Environment ◽  
Audio Output

Good vision is an expensive gift but now a day’s loss of vision is becoming common issue. Blind or visually impaired people does not have any conscious about the danger they are facing in their daily life. To help the blind people the visual world has to be transformed into the audio world with the potential to inform them about objects. Various challenges are faced by visually impaired patients even in the familiar environment. Visually impaired individuals are at drawback due to lack of sufficient information about their familiar environment. This project employs a Convolution Neural Network for recognition of pre-trained objects. This project employs in deep learning a deep Neural Network (DNN) for recognizing the object which is captured from the real world. The captured image is compared with some pre trained objects that is stored in dataset .The comparative of the object is based on the shape and size of an objects. In deep neural network, TensorFlow package using a model called Mobile Net SSD that is comparing the real time capture image with pre trained object based on shape, size of the object. If the image is matched with that trained object, it will display the name of the object. Then the name of the object is converted into audio output with the help of gTTS. This will helps to identify and detect what object is present in front of blind people and give output as audio.

scholarly journals Deep Learning Based Indian Currency Detection for Visually Challenged using VGG16

2020 ◽  
Vol 9 (2) ◽  
pp. 769-972
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Visually Impaired ◽  
Convolution Neural Network ◽  
Visually Impaired People ◽  
Impaired People ◽  
Learning Technique ◽  
Different Types ◽  
Visually Challenged ◽  
Banknote Recognition

Banknote recognition is a major problem faced by visually Challenged people. So we propose a system to help the visually Challenged people to identify the different types of Indian currencies through deep learning technique. In our proposed project, bank notes with different positions are directly fed into VGG 16, a pretrained model of convolution neural network which extracts deep features. From our work the visually impaired people will be able to recognize different types if Indian Currencies.

scholarly journals Hardware Design for Smart Walking Stick Supporting Neural Networks

2019 ◽  
Vol 8 (12S) ◽  
pp. 407-410
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
System Design ◽  
Visually Impaired ◽  
Hardware Design ◽  
Hardware System ◽  
Visually Impaired People ◽  
Video Frames ◽  
Impaired People ◽  
Walking Stick

This paper aims to bring out the efficient hardware system design to be used in walking stick by the visually impaired people especially to support the cutting edge software technologies to assist in their mobility. It is designed in such a way that it is convenient to handle and also to perform heavier programs without any degradation in accuracy. Hardware design uses Rasberry pi3 Model B for finding the obstacle and to find the distance of the obstacle. Pi camera is used to capture the video frames and feed each frame for processing. For real time object detection, the proposed system uses neural network to train the images.

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