Dr. K Ashfaq Ahmed

EDUCATION

M.Tech., Ph.D (Computer Science and Engineering)

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Engineering

Scopus Publications

Oral Cancer Detections and Classification Using Region Based Convolutional Neural Network
M Prema Kumar, K Ashfaq Ahmed, K Subash, Anurag Aeron
Tqcebt 2024 2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies 2024, 2024
Early detection dramatically increases the survival rate of oral cancer (OC). Artificial intelligence (AI) technology has garnered more attention in the field of diagnostic medicine in present periods. This study set out to assess the available data regarding AI's efficacy in OC diagnosis critically. Artificial intelligence diagnostic accuracy and capacity to detect early phases of OC were highlighted. In this project, performance indicators will be measured and oral cancer will be divided and classified using intelligent computing techniques. The role of oral cancer classification and detection to achieve a high recognition rate while leveraging the best theoretical components of oral cancer images, a newly established region-based Convolutional Neural Network (RCNN-COA) and the Chimp Optimization Algorithm were used to improve a Deep Learning Method. Then, using the recommended Chimp Optimization Algorithm (COA), a region-based convolutional neural network (R-CNN) classifier was trained using the acquired theoretical properties and the innovative image. A comparison of many deep learning and machine learning models' performances has been reported in a study. The findings imply that the deep learning model is capable of managing the problematic task of early oral malignant tumor detection.
Cancer disease prediction with support vector machine and random forest classification techniques
K Ashfaq Ahmed, Sultan Aljahdali, Nisar Hundewale, K Ishthaq Ahmed
Proceeding 2012 IEEE International Conference on Computational Intelligence and Cybernetics Cyberneticscom 2012, 2012
The Concept of classification and learning will suit well to medical applications, especially those that need complex diagnostic measurements. Therefore classification technique can be used for cancer disease prediction. This approach is very much interesting as it is part of a growing demand towards predictive diagnosis. From the available studies it is evident that classification and learning methods can be used effectively to improve the accuracy of predicting a disease and its recurrence. In the present work classification techniques namely Support Vector Machine [SVM] and Random Forest [RF] are used to learn, classify and compare cancer disease data with varying kernels and kernel parameters. Results with Support Vector Machines and Random Forest are compared for different data sets. The results with different kernels are tuned with proper parameters selection. Results are analyzed with confusion matrix.
A methodology for the abstraction of design components from the software requirement specification to the object oriented system
Syed Naimatullah Hussain, Nisar Hundewale, Sultan Aljahdali, K Ashfaq Ahmed
Icsess 2012 Proceedings of 2012 IEEE 3rd International Conference on Software Engineering and Service Science, 2012
The software developer's task begins with the procurement of project charter. This is a legal document containing details regarding the software requirement specification (SRS), cost and the schedule etc., of the project. The SRS of the organization is a text document incorporating the requirements of the organization. The software development of and information system is based on the SRS of the client organization. This paper attempts to abstracts design components (Object class name, Object methods, and its attributes. Actors and interfaces of actors) from software requirement specification. The objective of this paper is to develop a single semi automated methodology for the abstraction of different useable components from SRS, so that they can be transformed as model elements. To provide a semiotic environment for the design of model elements to the transformation of useable components.

RECENT SCHOLAR PUBLICATIONS

Oral Cancer Detections and Classification Using Region Based Convolutional Neural Network
MP Kumar, KA Ahmed, K Subash, A Aeron
2024 International Conference on Trends in Quantum Computing and Emerging … , 2024
2024.0
Ridge Regression based Missing Data Estimation with Dimensionality Reduction: Microarray Gene Expression Data
KA Ahmed, S Akthar
Webology 19 (1) , 2022
2022.0
An Ensembled Gradient Tree Boosting Regression Model for Estimating the Missing Data with Feature Selection
KA Ahmed, S Akthar
Design Engineering, 7841-7855 , 2021
2021.0
Missing Data Estimation with Extremely Randomized Tree Regressor and Dimensionality Reduction: Microarray Gene Expression Data
KA Ahmed, S Akthar
Advances in Mechanics 9 (3), 1680-1691 , 2021
2021.0
자율 주행 차 (AV) 의 비정상/이상 주행 조건 파악을 위한 연구
K Ahmed, S Hussain, JT KIM
한국 ITS 학회 학술대회, 197-200 , 2019
2019.0
Detection of single-trial EEG of the neural correlates of familiar faces recognition using machine-learning algorithms
A Alsufyani, R Alroobaea, A Ahmed
International Journal of Advanced Trends in Computer Science and Engineering … , 2019
2019.0
Citations: 7
Comparative prediction performance with support vector machine and random forest classification techniques
S Aljahdali, SN Hussain
International journal of computer applications 69 (11) , 2013
2013.0
Citations: 96
Cancer disease prediction with support vector machine and random forest classification techniques
KA Ahmed, S Aljahdali, N Hundewale, KI Ahmed
2012 IEEE International Conference on Computational Intelligence and … , 2012
2012.0
Citations: 11
A methodology for the abstraction of design components from the software requirement specification to the object oriented system. In international conference on software …
SN Hussain, N Hundewale, S Aljahdali, KA Ahmed
IEEE , 0
Citations: 4

MOST CITED SCHOLAR PUBLICATIONS

Comparative prediction performance with support vector machine and random forest classification techniques
S Aljahdali, SN Hussain
International journal of computer applications 69 (11) , 2013
2013.0
Citations: 96
Cancer disease prediction with support vector machine and random forest classification techniques
KA Ahmed, S Aljahdali, N Hundewale, KI Ahmed
2012 IEEE International Conference on Computational Intelligence and … , 2012
2012.0
Citations: 11
Detection of single-trial EEG of the neural correlates of familiar faces recognition using machine-learning algorithms
A Alsufyani, R Alroobaea, A Ahmed
International Journal of Advanced Trends in Computer Science and Engineering … , 2019
2019.0
Citations: 7
A methodology for the abstraction of design components from the software requirement specification to the object oriented system. In international conference on software …
SN Hussain, N Hundewale, S Aljahdali, KA Ahmed
IEEE , 0
Citations: 4
Oral Cancer Detections and Classification Using Region Based Convolutional Neural Network
MP Kumar, KA Ahmed, K Subash, A Aeron
2024 International Conference on Trends in Quantum Computing and Emerging … , 2024
2024.0
Ridge Regression based Missing Data Estimation with Dimensionality Reduction: Microarray Gene Expression Data
KA Ahmed, S Akthar
Webology 19 (1) , 2022
2022.0
An Ensembled Gradient Tree Boosting Regression Model for Estimating the Missing Data with Feature Selection
KA Ahmed, S Akthar
Design Engineering, 7841-7855 , 2021
2021.0
Missing Data Estimation with Extremely Randomized Tree Regressor and Dimensionality Reduction: Microarray Gene Expression Data
KA Ahmed, S Akthar
Advances in Mechanics 9 (3), 1680-1691 , 2021
2021.0
자율 주행 차 (AV) 의 비정상/이상 주행 조건 파악을 위한 연구
K Ahmed, S Hussain, JT KIM
한국 ITS 학회 학술대회, 197-200 , 2019
2019.0