Performance Improvement Using an Automation System for Segmentation of Multiple Parametric Features Based on Human Footprint

Human have always lived for the betterment of themselves but the bitter truth is that the process of modernisation has never focussed on making a safe society for women. The lack of self-reliance in women is one of the shortcomings of modernisation. An Advanced eyewear with an embedded camera will remove the barriers in a woman’s life. The combination of wireless communication with IoT sensors increases its scope of use. The People under threat would be intervened with the security officials or alert the emergency contacts saved previously. This paper introduces a security purpose eyewear with the required embedded technology to enhance the life style of a woman. This would bring in quicker and reliable information to the security officials. This would eventually hamper the victimizer from his cruel intentions by creating a fear of being watched.

Section: Existing Systemmentioning

confidence: 99%

Advanced Eyewear with Embedded Hardware for Woman Safety

Narendhiran.S¹,

Radhakrishnan.P²,

Elangovan.D³

2021

“…In this paper just as in [5] edge-based detection with the open street map is used to detect lanes which increases computation time. Hough Transform [9] is employed to identify the straight lane and the Curve fitting model detects the curve lane which increases the computation time [13][14].…”

Section: Related Workmentioning

confidence: 99%

Lane Detection and Tracking Algorithm Based on Curve Fitting Model

Rajakumar

Pandian

PremJacob.T

2021

Lane Detection is the fundamental vehicle driving system and self-driving. The proposed concept is to employ the pixel difference in the expected lane and the road backdrop to detach the lane from the road, and then the Curve fitting model is made use of in the segregated lanes to locate the straight line in the image as the lane line. This paper offers a lane detection method based on the Sobel filter and Curve-fitting model for lane line tracking in different conditions. The main objective is to improve the accuracy of the Xi’an city database and the KITTI vision benchmark suite dataset. To achieve this HLS color space was performed which identifies the lane by adding pixel values.

“…This survey gives different solutions for reducing the overfitting problem. In [10] build a deep learning study on skin disease image recognition.The review's finding is that data augmentation increases classification accuracy [11][12][13].…”

Section: Literature Surveymentioning

confidence: 99%

Data Set Preparation Using the Method of Data Augmentation for Classification of Skin Diseases

J.A¹,

MuraliBhaskharan²

2021

Skin disease are mostly ignored and provided less importance at the early stages. Some ignorance among people might lead to skin cancer. In existing approach, the increased skin disease are identified at the later stage using biopsy only. The inspection is performed manually by considering many histopathological features. This paper explains the development of a model which helps to detect the various skin diseases at early stage using neural networks. For classification and prediction purpose this paper using Convolutional Neural Network. For improving the accuracy of prediction we are going to do dataset preparation. Data augmentation is using for increasing the count size of the training data. So that the accuracy of the classification will increase and will get 97% result.