Saba, Tanzila.
Tanzila Saba researcher ORCID ID = 0000-0003-3138-3801
Saba, Tanzila, 19..-
VIAF ID: 3049162118002302320009 (Personal)
Permalink: http://viaf.org/viaf/3049162118002302320009
Preferred Forms
- 100 1 _ ‡a Saba, Tanzila
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- 100 1 _ ‡a Saba, Tanzila
- 100 1 _ ‡a Saba, Tanzila, ‡d 19..-
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- 100 0 _ ‡a Tanzila Saba ‡c researcher ORCID ID = 0000-0003-3138-3801
4xx's: Alternate Name Forms (2)
Works
Title | Sources |
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Artificial intelligence and Internet of Things : applications in smart healthcare | |
Automated lung nodule detection and classification based on multiple classifiers voting | |
Automated nuclei segmentation of malignant using level sets. | |
Automated techniques for blood vessels segmentation through fundus retinal images: A review | |
Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN). | |
Classification of acute lymphoblastic leukemia using deep learning | |
Cloud-based decision support system for the detection and classification of malignant cells in breast cancer using breast cytology images | |
Computer-assisted brain tumor type discrimination using magnetic resonance imaging features | |
Computer vision for microscopic skin cancer diagnosis using handcrafted and non-handcrafted features | |
Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion | |
Deep learning model integrating features and novel classifiers fusion for brain tumor segmentation | |
An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model. | |
Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing | |
An ensemble classification of exudates in color fundus images using an evolutionary algorithm based optimal features selection | |
Fundus image classification methods for the detection of glaucoma: A review | |
Intelligent bar chart plagiarism detection in documents. | |
Intelligent computing applications for COVID-19 : predictions, diagnosis, and prevention | |
Intelligent microscopic approach for identification and recognition of citrus deformities | |
Internet-of-Things-Based Suspicious Activity Recognition Using Multimodalities of Computer Vision for Smart City Security | |
Lungs nodule detection framework from computed tomography images using support vector machine | |
Microscopic abnormality classification of cardiac murmurs using ANFIS and HMM. | |
Microscopic brain tumor detection and classification using 3D CNN and feature selection architecture | |
Microscopic malaria parasitemia diagnosis and grading on benchmark datasets | |
Mobile-Health Applications for the Efficient Delivery of Health Care Facility to People with Dementia (PwD) and Support to Their Carers: A Survey | |
Multi-Images Encryption Scheme Based on 3D Chaotic Map and Substitution Box | |
Multifocus watermarking approach based on discrete cosine transform. | |
A novel classification scheme to decline the mortality rate among women due to breast tumor. | |
Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear | |
Prognostic models in healthcare: AI and statistical approaches / Tanzila Saba, Amjad Rehman, Sudipta Roy, editors. - Singapore, © 2022. | |
Real time anomalies detection in crowd using convolutional long short-term memory network | |
Real-Time Diagnosis System of COVID-19 Using X-Ray Images and Deep Learning | |
Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction | |
Reliability Analysis for Electronic Devices Using Generalized Exponential Distribution | |
Removal of pectoral muscle based on topographic map and shape-shifting silhouette | |
Retinal imaging analysis based on vessel detection. | |
Retraction: Implications of E-learning systems and self-efficiency on students outcomes: a model approach | |
A Revisit of Internet of Things Technologies for Monitoring and Control Strategies in Smart Agriculture | |
Rouleaux red blood cells splitting in microscopic thin blood smear images via local maxima, circles drawing, and mapping with original RBCs. |