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Nagamma Patil
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2020 – today
- 2024
- [j26]Tulasi Gayatri Devi, Nagamma Patil:
Optimization-based convolutional neural model for the classification of white blood cells. J. Big Data 11(1): 90 (2024) - [j25]Tarushi Jat, Nagamma Patil, Prajna Bhat
:
Detection of heart arrhythmia with electrocardiography. Netw. Model. Anal. Health Informatics Bioinform. 13(1): 57 (2024) - [j24]Mukul Kadaskar
ANet: Nuclei Instance Segmentation and Classification with Attention-Based Network. SN Comput. Sci. 5(4): 348 (2024) - 2023
- [j23]C. K. Sunil
Systematic study on deep learning-based plant disease detection or classification. Artif. Intell. Rev. 56(12): 14955-15052 (2023) - [j22]C. K. Sunil
Tomato plant disease classification using Multilevel Feature Fusion with adaptive channel spatial and pixel attention mechanism. Expert Syst. Appl. 228: 120381 (2023) - [j21]Tulasi Gayatri Devi
Segmentation and classification of white blood cancer cells from bone marrow microscopic images using duplet-convolutional neural network design. Multim. Tools Appl. 82(23): 35277-35299 (2023) - [j20]Tulasi Gayatri Devi
Real-time microscopy image-based segmentation and classification models for cancer cell detection. Multim. Tools Appl. 82(23): 35969-35994 (2023) - [j19]Prajna Bhat
An exhaustive review of computational prediction techniques for PPI sites, protein locations, and protein functions. Netw. Model. Anal. Health Informatics Bioinform. 12(1): 31 (2023) - [j18]Shubham Agrawal
Utilizing Deep Learning Models and Transfer Learning for COVID-19 Detection from X-Ray Images. SN Comput. Sci. 4(4): 326 (2023) - [j17]Suyash Chintawar
OntoPred: An Efficient Attention-Based Approach for Protein Function Prediction Using Skip-Gram Features. SN Comput. Sci. 4(5): 666 (2023) - [j16]Mukul Kadaskar
Image Analysis of Nuclei Histopathology Using Deep Learning: A Review of Segmentation, Detection, and Classification. SN Comput. Sci. 4(5): 698 (2023) - [c18]Rosamma K. S, Nagamma Patil:
Measuring the Quality of Text Summarization: A Survey of Evaluation Approaches. OCIT 2023: 290-296 - [c17]Rosamma K. S, Nagamma Patil:
Pioneering Frontiers in Natural Language Processing: Exploring Promising Areas and Emerging Applications. OCIT 2023: 640-647 - [c16]Mukul Kadaskar, Nagamma Patil:
Nuclei Segmentation using EfficientNetV2 and Convolutional Block Attention Module. ICCCNT 2023: 1-5 - [c15]Mukul Kadaskar, Nagamma Patil:
Nuclei Classification in Histopathology Images Using Fuzzy Ensemble of Convolutional Neural Networks. ICCCNT 2023: 1-6 - [c14]Kausthub Thekke Madathil, Abhinav Dugar, Nagamma Patil, Unnikrishnan Cheramangalath:
Optimizing Machine Learning Operators and Models for Specific Hardware Using Apache-TVM. ICCCNT 2023: 1-7 - 2022
- [j15]C. K. Sunil
Cardamom Plant Disease Detection Approach Using EfficientNetV2. IEEE Access 10: 789-804 (2022) - [j14]Manjunath K. Vanahalli, Nagamma Patil:
An efficient colossal closed itemset mining algorithm for a dataset with high dimensionality. J. King Saud Univ. Comput. Inf. Sci. 34(6 Part A): 2798-2808 (2022) - [j13]Sanjay S. Bankapur
An Effective Multi-Label Protein Sub-Chloroplast Localization Prediction by Skipped-Grams of Evolutionary Profiles Using Deep Neural Network. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1449-1458 (2022) - [i1]Anirudha Rayasam, Nagamma Patil:
Robust self-healing prediction model for high dimensional data. CoRR abs/2210.01788 (2022) - 2021
- [j12]Aditya Jayasimha
An effective feature extraction with deep neural network architecture for protein-secondary-structure prediction. Netw. Model. Anal. Health Informatics Bioinform. 10(1): 58 (2021) - [j11]Sanjay S. Bankapur
Enhanced Protein Structural Class Prediction Using Effective Feature Modeling and Ensemble of Classifiers. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2409-2419 (2021) - [c13]Rakesh Pavan, Madhumitha Nara, Suhas Gopinath, Nagamma Patil:
Bayesian Optimization and Gradient Boosting to Detect Phishing Websites. CISS 2021: 1-5 - [c12]Tulasi Gayatri Devi
Survey of Leukemia Cancer Cell Detection Using Image Processing. CVIP (1) 2021: 468-488 - [c11]Kains Praveen K, Nagamma Patil, Srikanth C. S, Vikas J:
M-CAD: Towards Multi-Categorical Auto Diagnosis of Varied Diseases using Deep Learning. IRI 2021: 223-227 - 2020
- [j10]Prince Kumar
An enhanced protein secondary structure prediction using deep learning framework on hybrid profile based features. Appl. Soft Comput. 86 (2020) - [j9]Kiranpreet Kaur, Nagamma Patil:
A fast and novel approach based on grouping and weighted mRMR for feature selection and classification of protein sequence data. Int. J. Data Min. Bioinform. 23(1): 47-61 (2020) - [j8]Sanjay S. Bankapur
ProgSIO-MSA: Progressive-based single iterative optimization framework for multiple sequence alignment using an effective scoring system. J. Bioinform. Comput. Biol. 18(2): 2050005:1-2050005:28 (2020) - [j7]Manjunath K. Vanahalli, Nagamma Patil:
Distributed load balancing frequent colossal closed itemset mining algorithm for high dimensional dataset. J. Parallel Distributed Comput. 144: 136-152 (2020) - [c10]C. K. Sunil
Empirical Study on Multi Convolutional Layer-based Convolutional Neural Network Classifier for Plant Leaf Disease Detection. ICIIS 2020: 460-465
2010 – 2019
- 2019
- [j6]Tushaar Gangavarapu
A novel filter-wrapper hybrid greedy ensemble approach optimized using the genetic algorithm to reduce the dimensionality of high-dimensional biomedical datasets. Appl. Soft Comput. 81 (2019) - [j5]Manjunath K. Vanahalli
An efficient dynamic switching algorithm for mining colossal closed itemsets from high dimensional datasets. Data Knowl. Eng. 123 (2019) - [j4]Manjunath K. Vanahalli
An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets. Inf. Sci. 496: 343-362 (2019) - 2018
- [j3]Medhini Narasimhan, Balaji Balasubramanian, Suryansh D. Kumar, Nagamma Patil:
EGA-FMC: enhanced genetic algorithm-based fuzzy k-modes clustering for categorical data. Int. J. Bio Inspired Comput. 11(4): 219-228 (2018) - [c9]Sanjay S. Bankapur
Protein Secondary Structural Class Prediction Using Effective Feature Modeling and Machine Learning Techniques. BIBE 2018: 18-21 - [c8]Manjunath K. Vanahalli
Distributed Mining of Significant Frequent Colossal Closed Itemsets from Long Biological Dataset. ISDA (1) 2018: 891-902 - [c7]Ujjwal Pasupulety
Feature Selection Using Fast Ensemble Learning for Network Intrusion Detection. ISDA (1) 2018: 967-977 - 2017
- [c6]Sanjay S. Bankapur
Position-Residue Specific Dynamic Gap Penalty Scoring Strategy for Multiple Sequence Alignment. CSBio 2017: 42-45 - [c5]Akanksha Kumari, Ashish Kumar Singh, Nagamma Patil:
Travel Recommendation System Using Geotagged Photos. ICCCT 2017: 22-26 - [c4]Sanjay S. Bankapur
Efficient and Effective Multiple Protein Sequence Alignment Model Using Dynamic Progressive Approach with Novel Look Back Ahead Scoring System. PReMI 2017: 397-404 - 2015
- [c3]Amimul Ehsan, Nagamma Patil:
Normalized weighted and reverse weighted correlation based Apriori algorithm. ICACCI 2015: 841-847 - 2013
- [j2]Nagamma Patil, Durga Toshniwal, Kumkum Garg:
Clustering genome data based on approximate matching. Int. J. Data Anal. Tech. Strateg. 5(2): 122-147 (2013) - 2012
- [j1]Nagamma Patil, Durga Toshniwal, Kumkum Garg:
Effective framework for protein structure prediction. Int. J. Funct. Informatics Pers. Medicine 4(1): 69-79 (2012) - 2011
- [c2]Nagamma Patil, Durga Toshniwal, Kumkum Garg:
Species identification based on approximate matching. Bangalore Compute Conf. 2011: 30 - [c1]Satish Gajawada, Durga Toshniwal, Nagamma Patil, Kumkum Garg:
Optimal Clustering Method Based on Genetic Algorithm. SocProS (2) 2011: 295-303
Coauthor Index
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last updated on 2024-10-23 20:26 CEST by the dblp team
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