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ORCIDJyostna Devi Bodapati
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2020 – today
- 2024
[j21]Jyostna Devi Bodapati
, Bharadwaj Bagepalli Balaji:
Self-adaptive stacking ensemble approach with attention based deep neural network models for diabetic retinopathy severity prediction. Multim. Tools Appl. 83(1): 1083-1102 (2024)- [j20]Jyostna Devi Bodapati, Bharadwaj Bagepalli Balaji:
TumorAwareNet: Deep representation learning with attention based sparse convolutional denoising autoencoder for brain tumor recognition. Multim. Tools Appl. 83(8): 22099-22117 (2024) - [j19]Veeranjaneyulu Naralasetti, Jyostna Devi Bodapati:
Adaptive ensembling of multi-modal deep spatial representations for diabetic retinopathy diagnosis. Multim. Tools Appl. 83(26): 68467-68486 (2024) - [j18]Shaik Nagur Shareef, Teja Krishna Cherukuri, N. Veeranjaneulu, Jyostna Devi Bodapati:
Medtransnet: advanced gating transformer network for medical image classification. Mach. Vis. Appl. 35(4): 73 (2024) - 2022
- [j17]Jyostna Devi Bodapati:
Stacked convolutional auto-encoder representations with spatial attention for efficient diabetic retinopathy diagnosis. Multim. Tools Appl. 81(22): 32033-32056 (2022) - 2021
- [j16]Jyostna Devi Bodapati, Shaik Nagur Shareef, Veeranjaneyulu Naralasetti, Nirupama Bhat Mundukur:
MSENet: Multi-Modal Squeeze-and-Excitation Network for Brain Tumor Severity Prediction. Int. J. Pattern Recognit. Artif. Intell. 35(7): 2157005:1-2157005:22 (2021) - [j15]Jyostna Devi Bodapati:
Modified self-training based statistical models for image classification and speaker identification. Int. J. Speech Technol. 24(4): 1007-1015 (2021) - [j14]Jyostna Devi Bodapati, Shaik Nagur Shareef, Veeranjaneyulu Naralasetti:
Composite deep neural network with gated-attention mechanism for diabetic retinopathy severity classification. J. Ambient Intell. Humaniz. Comput. 12(10): 9825-9839 (2021) - [j13]Jyostna Devi Bodapati, Shaik Nagur Shareef, Veeranjaneyulu Naralasetti, Nirupama Bhat Mundukur:
Joint training of two-channel deep neural network for brain tumor classification. Signal Image Video Process. 15(4): 753-760 (2021) - [j12]Jyostna Devi Bodapati, Shaik Nagur Shareef, Veeranjaneyulu Naralasetti:
Deep convolution feature aggregation: an application to diabetic retinopathy severity level prediction. Signal Image Video Process. 15(5): 923-930 (2021) - [j11]Jyostna Devi Bodapati:
SAE-PD-Seq: sequence autoencoder-based pre-training of decoder for sequence learning tasks. Signal Image Video Process. 15(7): 1453-1459 (2021) - [j10]Veeranjaneyulu Naralasetti, Reshmi Khadherbhi Shaik, Gayatri Katepalli, Jyostna Devi Bodapati:
Deep Learning Models for Pneumonia Identification and Classification Based on X-Ray Images. Traitement du Signal 38(3): 903-909 (2021) - 2020
- [j9]Suvarna Buradagunta, Jyostna Devi Bodapati, Nirupama Bhat Mundukur, Shaik Salma:
Performance Comparison of Sorting Algorithms with Random Numbers as Inputs. Ingénierie des Systèmes d Inf. 25(1): 113-117 (2020) - [j8]Jyostna Devi Bodapati, Annepu Vijay, Naralasetti Veeranjaneyulu:
Brain Tumor Detection Using Deep Features in the Latent Space. Ingénierie des Systèmes d Inf. 25(2): 259-265 (2020) - [j7]Naralasetti Veeranjaneyulu, Jyostna Devi Bodapati, Suvarna Buradagunta:
Classifying Limited Resource Data Using Semi-supervised SVM. Ingénierie des Systèmes d Inf. 25(3): 391-395 (2020) - [j6]Venkatesulu Dondeti, Jyostna Devi Bodapati, Shaik Nagur Shareef, Veeranjaneyulu Naralasetti:
Deep Convolution Features in Non-linear Embedding Space for Fundus Image Classification. Rev. d'Intelligence Artif. 34(3): 307-313 (2020) - [i1]Jyostna Devi Bodapati, Naralasetti Veeranjaneyulu, Shaik Nagur Shareef, Saqib Hakak, Muhammad Bilal, Praveen Kumar Reddy Maddikunta, Ohyun Jo:
Blended Multi-Modal Deep ConvNet Features for Diabetic Retinopathy Severity Prediction. CoRR abs/2006.00197 (2020)
2010 – 2019
- 2019
- [j5]Jyostna Devi Bodapati, Naralasetti Veeranjaneyulu, Shaik Nagur Shareef:
Sentiment Analysis from Movie Reviews Using LSTMs. Ingénierie des Systèmes d Inf. 24(1): 125-129 (2019) - [j4]Jyostna Devi Bodapati, Venkata Rama Krishna Sajja, Nirupama Bhat Mundukur, Naralasetti Veeranjaneyulu:
Robust Cluster-then-label (RCTL) Approach for Heart Disease Prediction. Ingénierie des Systèmes d Inf. 24(3): 255-260 (2019) - [j3]Kalpana Polisetty, Kiran Kumar Paidipati, Jyostna Devi Bodapati:
Modelling of Monthly Rainfall Patterns in the North-West India Using SVM. Ingénierie des Systèmes d Inf. 24(4): 391-395 (2019) - [j2]Jyostna Devi Bodapati, Veeranjaneyulu Naralasetti:
Feature Extraction and Classification UsingDeep Convolutional Neural Networks. J. Cyber Secur. Mobil. 8(2): 261-276 (2019) - [j1]Naralasetti Veeranjaneyulu, Gavini Srivalli, Jyostna Devi Bodapati:
Home Automation and Security System Using IOT. Rev. d'Intelligence Artif. 33(1): 21-24 (2019) - 2016
- [c2]Jyostna Devi Bodapati, Naralasetti Veeranjaneyulu:
Abnormal Network Traffic Detection Using Support Vector Data Description. FICTA (1) 2016: 497-506 - 2010
- [c1]B. Jyostna Devi, Naralasetti Veeranjaneyulu, K. V. K. Kishore:
A novel face recognition system based on combining eigenfaces with fisher faces using wavelets. Biometrics Technology 2010: 44-51
Coauthor Index
aka: Naralasetti Veeranjaneyulu
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