scholarly journals Pothole Detection System

2020 ◽  
Vol 9 (6) ◽  
pp. 89-92
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Efficient Method ◽  
Mobile Application ◽  
Detection System ◽  
The Road ◽  
Communication Gap ◽  
The Government ◽  
Pothole Detection

Potholes are a common nuisance that most people have had the displeasure of coming across. These bowl-shaped cavities in the road cause a large proportion of automobile related accidents, either directly or indirectly. Begetting the process of getting a pothole covered/fixed is a time consuming one that involves informing the appropriate authorities and having them take action. Implementing a system that involves citizens in the process of detecting pothole is what is being envisioned. The system includes a mobile application which is capable of taking a photo, this photo is then sent to a backend server where it is processed by a neural network model capable of detecting potholes. If any potholes are detected in the photo then the photo is saved along with its geolocation and forwarded to the appropriate authorities thus providing an efficient method of identifying potholes and removing the communication gap between the government and its citizens.

scholarly journals Pothole Detection Using Yolo V3: A Deep Learning Approach

2021 ◽  
Vol 9 (VII) ◽  
pp. 1989-1993
Author(s):  
Deepa A L
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Mobile Application ◽  
Detection System ◽  
Learning Approach ◽  
The Road ◽  
The Look ◽  
Pothole Detection

Potholes on roads constitute a serious problem for citizens acting as pedestrians furthermore as vehicular drivers. Government bodies which carries with it engineers and workers are responsible to detect damages on roads. Manually assessing every single a part of the road is very time- consuming, requires lots of manpower and hence it cannot be done efficiently. the tactic to repair this issue by automating the detection. The study focuses on collecting and analyzing the dataset of potholes to coach a convolutional neural network. the thing detection system tiny YOLOv3 is employed for detecting the potholes. the look of a system is identified which may be used for developing a mobile application for detection and presenting a visualized view of the potholes.

scholarly journals Cloud based mobile solution for early detection of Skin Cancer using Artificial Intelligence

2021 ◽  
pp. 312-324
Author(s):  
Pawan Sonawane ◽  
Sahel Shardhul ◽  
Raju Mendhe
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Skin Cancer ◽  
Early Detection ◽  
Transfer Learning ◽  
Network Model ◽  
Neural Network Model ◽  
Mobile Application ◽  
Low Cost ◽  
Skin Tumors

The vast majority of skin cancer deaths are from melanoma, with about 1.04 million cases annually. Early detection of the same can be immensely helpful in order to try to cure it. But most of the diagnosis procedures are either extremely expensive or not available to a vast majority, as these centers are concentrated in urban regions only. Thus, there is a need for an application that can perform a quick, efficient, and low-cost diagnosis. Our solution proposes to build a server less mobile application on the AWS cloud that takes the images of potential skin tumors and classifies it as either Malignant or Benign. The classification would be carried out using a trained Convolution Neural Network model and Transfer learning (Inception v3). Several experiments will be performed based on Morphology and Color of the tumor to identify ideal parameters.

Grey RBF Neural Network Forecasting on LV under the View of Government Responsibility

2012 ◽  
Vol 452-453 ◽  
pp. 700-704
Author(s):  
Feng Rong Zhang ◽  
Annik Magerholm Fet ◽  
Xin Wei Xiao
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Development Policy ◽  
Rbf Neural Network ◽  
Good Method ◽  
Government Responsibility ◽  
Long Period ◽  
The Government

At present, the domestic research on the scale of macroscopic logistics has yet belonged to the blankness, therefore, this research tries using LV in circulation and LV in stock to measure the logistics volume and forecasting it in a long period. In order to overcome the phenomenon of “floating upward” in long-term period, this paper establish the improved Grey RBF to forecast the LV next 5-10 year in Jilin province of China. The results show that the increased circulation of goods is the main reason leading to increased logistics volume, and the simulation also shows that the improved gray RBF neural network model is a good method for the government to establish the logistics development policy.

Using neural network model to estimate the rental price of residential properties

2019 ◽  
Vol 24 (2) ◽  
pp. 217-230
Author(s):  
Olalekan Shamsideen Oshodi ◽  
Wellington Didibhuku Thwala ◽  
Tawakalitu Bisola Odubiyi ◽  
Rotimi Boluwatife Abidoye ◽  
Clinton Ohis Aigbavboa
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Predictive Accuracy ◽  
Content Type ◽  
The Neural Network ◽  
Residential Properties ◽  
African Context ◽  
Neural Network Algorithm ◽  
The Government

Purpose Estimation of the rental price of a residential property is important to real estate investors, financial institutions, buyers and the government. These estimates provide information for assessing the economic viability and the tax accruable, respectively. The purpose of this study is to develop a neural network model for estimating the rental prices of residential properties in Cape Town, South Africa. Design/methodology/approach Data were collected on 14 property attributes and the rental prices were collected from relevant sources. The neural network algorithm was used for model estimation and validation. The data relating to 286 residential properties were collected in 2018. Findings The results show that the predictive accuracy of the developed neural network model is 78.95 per cent. Based on the sensitivity analysis of the model, it was revealed that balcony and floor area have the most significant impact on the rental price of residential properties. However, parking type and swimming pool had the least impact on rental price. Also, the availability of garden and proximity of police station had a low impact on rental price when compared to balcony. Practical implications In the light of these results, the developed neural network model could be used to estimate rental price for taxation. Also, the significant variables identified need to be included in the designs of new residential homes and this would ensure optimal returns to the investors. Originality/value A number of studies have shown that crime influences the value of residential properties. However, to the best of the authors’ knowledge, there is limited research investigating this relationship within the South African context.

The organization of masses’ spontaneous sports activities based on BP neural network model

2021 ◽  
pp. 1-9
Author(s):  
Xiangling Wang ◽  
Xiangying Wang
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Chinese Government ◽  
Beijing City ◽  
The Government ◽  
The Masses ◽  
Bp Neural Network Model ◽  
Sports Activities

Chinese government has made huge efforts in improving people’s spiritual and cultural life, but effects are far from satisfactory. The organization of masses’ spontaneous sports activities is the basic countermeasure to improve this situation, for it can not only reduce the government economic investment, but also meet the needs of people’s physical exercises. This paper takes five parks – Sunrise Park, Temple of Heaven Park, Beihai Park, Yu Yuantan Park and Purple Bamboo Park – in Beijing city as research objects, and makes the research on the current developing situations of the organization of masses’ spontaneous sports activities. Based on BP neural network model, the paper makes analysis according to the masses’ weekly exercises frequency and duration in the above-mentioned five parks. The results show that the organization of masses’ spontaneous sports activities in Temple of Heaven Park and Beihai Park is going quite well, while the situation of Sunrise Park and Purple Bamboo Park is far from that good.

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