Rashi Agarwal
Biographic Data
| ID | 8430270 |
|---|---|
| NAME | Rashi Agarwal |
| GIVEN NAMES | Rashi |
| FAMILY NAME | Agarwal |
| SIGNATURE | AGARWAL R |
| AFFILIATIONS | Chhatrapati Shahu Ji Maharaj University |
| ORCID | 0000-0002-5768-5894 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Minimum relevant features to obtain AI explainable system for predicting breast cancer in WDBC
The potential to explain why a machine learning model produces a certain prediction in incomprehensible terms is becoming increasingly crucial, as it provides accountability and confidence in the algorithm's decision-making process. The interpretation of complex models is difficult. Various approaches to dealing with this issue are being offered. These problems are typically handled in tree ensemble methods by assigning priority levels to input f…
Identifying highly vulnerable mosquito breeding sites using machine learning and drone based aerial survey
This study deals with Drone based Aerial Survey in analyzing and identification of highly vulnerable mosquito breeding sites at Buckingham canal Chepauk, Chennai. It is small section of Buckingham canal studied using the drone for capturing the images and furtherly images were processed for identifying the sites prone to breeding of mosquitos. Approach used here of capturing images and classifying the vulnerable sites, using a machine learning ap…
No prominent works on this page.
Minimum relevant features to obtain AI explainable system for predicting breast cancer in WDBC
The potential to explain why a machine learning model produces a certain prediction in incomprehensible terms is becoming increasingly crucial, as it provides accountability and confidence in the algorithm's decision-making process. The interpretation of complex models is difficult. Various approaches to dealing with this issue are being offered. These problems are typically handled in tree ensemble methods by assigning priority levels to input f…
Identifying highly vulnerable mosquito breeding sites using machine learning and drone based aerial survey
This study deals with Drone based Aerial Survey in analyzing and identification of highly vulnerable mosquito breeding sites at Buckingham canal Chepauk, Chennai. It is small section of Buckingham canal studied using the drone for capturing the images and furtherly images were processed for identifying the sites prone to breeding of mosquitos. Approach used here of capturing images and classifying the vulnerable sites, using a machine learning ap…
Artificial Intelligence (2 works) · Computer Science (2 works) · Machine learning (2 works) · Support vector machine (2 works) · Artificial neural network (1 work) · Computer vision (1 work) · Convolutional neural network (1 work) · Data mining (1 work) · Decision tree (1 work) · Detector (1 work)