Her primary scientific interests are in Artificial intelligence, Particle swarm optimization, Machine learning, Image segmentation and Artificial neural network. Her Artificial intelligence research includes elements of Information processing, Computer vision and Pattern recognition. Her study looks at the intersection of Pattern recognition and topics like Thresholding with Jaccard index and Active contour model.
Her research investigates the link between Particle swarm optimization and topics such as Genetic algorithm that cross with problems in Context. Amira S. Ashour has included themes like Classifier, Fuzzy partitioning, Data mining and Sensitivity in her Machine learning study. Her Artificial neural network study integrates concerns from other disciplines, such as Local optimum, Reduction and Fuzzy classifier.
Her primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Cluster analysis. Her Artificial intelligence research integrates issues from Machine learning and Particle swarm optimization. In her research on the topic of Particle swarm optimization, Evolutionary algorithm is strongly related with Genetic algorithm.
Her Pattern recognition research incorporates elements of Contextual image classification, Image, Thresholding and Fuzzy logic. Her study ties her expertise on Image processing together with the subject of Segmentation. Her study of Multilayer perceptron is a part of Artificial neural network.
Amira S. Ashour mainly focuses on Artificial intelligence, Pattern recognition, Segmentation, Cluster analysis and Fuzzy logic. Domain is closely connected to Machine learning in her research, which is encompassed under the umbrella topic of Artificial intelligence. Her work deals with themes such as Contextual image classification and Artificial neural network, which intersect with Pattern recognition.
Her work carried out in the field of Segmentation brings together such families of science as Image processing, Genetic algorithm, Centroid and Histogram. She interconnects Pixel, Silhouette, Filter and Jaccard index in the investigation of issues within Cluster analysis. Her studies deal with areas such as Entropy, MATLAB, Cardiac pacemaker and Pattern recognition as well as Fuzzy logic.
Amira S. Ashour mainly investigates Artificial intelligence, Pattern recognition, Segmentation, Cluster analysis and Convolutional neural network. Her Artificial intelligence study frequently draws connections between adjacent fields such as Mathematical optimization. Her research in Pattern recognition intersects with topics in Contextual image classification, Artificial neural network, Deep learning and Feature.
Her studies in Segmentation integrate themes in fields like Histogram, Centroid, Jaccard index and Genetic algorithm. She focuses mostly in the field of Cluster analysis, narrowing it down to topics relating to Pixel and, in certain cases, Euclidean distance, Mixture model, Silhouette and Algorithm. The concepts of her Convolutional neural network study are interwoven with issues in Classifier, Convolution and Cirrhosis.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Particle swarm optimization trained neural network for structural failure prediction of multistoried RC buildings
Sankhadeep Chatterjee;Sarbartha Sarkar;Sirshendu Hore;Nilanjan Dey.
Neural Computing and Applications (2017)
Multi-level image thresholding using Otsu and chaotic bat algorithm
Suresh Chandra Satapathy;N. Sri Madhava Raja;V. Rajinikanth;Amira S. Ashour.
Neural Computing and Applications (2018)
Developing residential wireless sensor networks for ECG healthcare monitoring
Nilanjan Dey;Amira S. Ashour;Fuqian Shi;Simon James Fong.
IEEE Transactions on Consumer Electronics (2017)
Internet of Things and Big Data Analytics Toward Next-Generation Intelligence
Nilanjan Dey;Aboul Ella Hassanien;Chintan Bhatt;Amira S. Ashour.
Internet of Things and Big Data Technologies for Next Generation Healthcare
Chintan Bhatt;Nilanjan Dey;Amira S. Ashour.
Automated stratification of liver disease in ultrasound
Luca Saba;Nilanjan Dey;Amira S. Ashour;Sourav Samanta.
Computer Methods and Programs in Biomedicine (2016)
Social Group Optimization Supported Segmentation and Evaluation of Skin Melanoma Images
Nilanjan Dey;Venkatesan Rajinikanth;Amira S. Ashour;João Manuel R. S. Tavares.
An Integrated Interactive Technique for Image Segmentation using Stack based Seeded Region Growing and Thresholding
Sirshendu Hore;Souvik Chakraborty;Sankhadeep Chatterjee;Nilanjan Dey.
International Journal of Electrical and Computer Engineering (2016)
Internet of Things Based Wireless Body Area Network in Healthcare
G. Elhayatmy;Nilanjan Dey;Amira S. Ashour.
Parameter Optimization for Local Polynomial Approximation based Intersection Confidence Interval Filter Using Genetic Algorithm: An Application for Brain MRI Image De-Noising
Nilanjan Dey;Amira S. Ashour;Samsad Beagum;Dimitra Sifaki Pistola.
Journal of Imaging (2015)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: