H1DBi-R Net: Hybrid 1D Bidirectional RNN for Efficient Diabetic Retinopathy Detection and Classification

[1]  Mahesh Gour,et al.  XCapsNet: A deep neural network for automated detection of diabetic retinopathy , 2023, Int. J. Imaging Syst. Technol..

[2]  R. Kalaiselvi,et al.  ESLO: Enhanced sea lion optimization based bi‐directional CNN‐RNN for accurate detection of diabetic retinopathy , 2022, Concurr. Comput. Pract. Exp..

[3]  Abdelmgeid A. Ali,et al.  An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm , 2022, Neural Computing and Applications.

[4]  Md. Shamim Anower,et al.  Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images , 2022, Comput. Biol. Medicine.

[5]  Farhad Soleimanian Gharehchopogh,et al.  A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems , 2021, The Journal of Supercomputing.

[6]  Haidi Ibrahim,et al.  Neovascularization Detection and Localization in Fundus Images Using Deep Learning , 2021, Sensors.

[7]  Feng Li,et al.  Deep learning-based automated detection for diabetic retinopathy and diabetic macular oedema in retinal fundus photographs , 2021, Eye.

[8]  Rajiv Raman,et al.  Deep learning architecture based on segmented fundus image features for classification of diabetic retinopathy , 2021, Biomed. Signal Process. Control..

[9]  Jibin Wang,et al.  An intelligent computer-aided approach for atrial fibrillation and atrial flutter signals classification using modified bidirectional LSTM network , 2021, Inf. Sci..

[10]  L. V. Narasimha Prasad,et al.  Diabetic retinopathy detection and classification using capsule networks , 2021, Complex & Intelligent Systems.

[11]  ARUN T NAIR,et al.  AUTOMATED SCREENING OF DIABETIC RETINOPATHY WITH OPTIMIZED DEEP CONVOLUTIONAL NEURAL NETWORK: ENHANCED MOTH FLAME MODEL , 2021 .

[12]  Sanjay Ganorkar,et al.  Diabetic Retinopathy Detection Using Optimization Assisted Deep Learning Model: Outlook on Improved Grey Wolf Algorithm , 2021, Int. J. Image Graph..

[13]  S. S. Teoh,et al.  Blood Vessel Segmentation in Fundus Images Using Hessian Matrix for Diabetic Retinopathy Detection , 2020, 2020 11th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON).

[14]  P. Saranya,et al.  Automatic detection of non-proliferative diabetic retinopathy in retinal fundus images using convolution neural network , 2020 .

[15]  Fei Shi,et al.  Coarse-to-fine classification for diabetic retinopathy grading using convolutional neural network , 2020, Artif. Intell. Medicine.

[16]  S. Gayathri,et al.  Automated classification of diabetic retinopathy through reliable feature selection , 2020, Physical and Engineering Sciences in Medicine.

[17]  Sherin M. Youssef,et al.  HyCAD-OCT: A Hybrid Computer-Aided Diagnosis of Retinopathy by Optical Coherence Tomography Integrating Machine Learning and Feature Maps Localization , 2020 .

[18]  Suresh Chandra Satapathy,et al.  Automated detection of diabetic retinopathy using convolutional neural networks on a small dataset , 2020, Pattern Recognit. Lett..

[19]  Deepak Gupta,et al.  Automated detection and classification of fundus diabetic retinopathy images using synergic deep learning model , 2020, Pattern Recognit. Lett..

[20]  Saket S. Chaturvedi,et al.  Automated Diabetic Retinopathy Grading using Deep Convolutional Neural Network , 2020, ArXiv.

[21]  Eswaran Perumal,et al.  Deep neural network with moth search optimization algorithm based detection and classification of diabetic retinopathy images , 2020, SN Applied Sciences.

[22]  R. Vidhyavathi,et al.  Deep neural network with moth search optimization algorithm based detection and classification of diabetic retinopathy images , 2020, SN Applied Sciences.

[23]  Praveen Kumar Reddy Maddikunta,et al.  Early Detection of Diabetic Retinopathy Using PCA-Firefly Based Deep Learning Model , 2020, Electronics.

[24]  R. S. Sabeenian,et al.  Modified Alexnet architecture for classification of diabetic retinopathy images , 2019, Comput. Electr. Eng..

[25]  Seifedine Kadry,et al.  Diagnosis of diabetic retinopathy using multi level set segmentation algorithm with feature extraction using SVM with selective features , 2019, Multimedia Tools and Applications.

[26]  Serkan Kiranyaz,et al.  A Generic Intelligent Bearing Fault Diagnosis System Using Compact Adaptive 1D CNN Classifier , 2018, Journal of Signal Processing Systems.

[27]  Omer Deperlioglu,et al.  An enhanced diabetic retinopathy detection and classification approach using deep convolutional neural network , 2019, Neural Computing and Applications.

[28]  Obaida M. Al-Hazaimeh,et al.  An effective image processing method for detection of diabetic retinopathy diseases from retinal fundus images , 2018 .

[29]  R. J. Kuo,et al.  Five discrete symbiotic organisms search algorithms for simultaneous optimization of feature subset and neighborhood size of KNN classification models , 2018, Appl. Soft Comput..

[30]  Daniel S. Kermany,et al.  Identifying Medical Diagnoses and Treatable Diseases by Image-Based Deep Learning , 2018, Cell.

[31]  Abdullah G. Alharbi,et al.  BHyPreC: A Novel Bi-LSTM Based Hybrid Recurrent Neural Network Model to Predict the CPU Workload of Cloud Virtual Machine , 2021, IEEE Access.

[32]  Vadlamani Ravi,et al.  Diabetic Retinopathy Detection Using Transfer Learning and Deep Learning , 2020, FICTA.

[33]  S. Shakya,et al.  Detection And Classification Of Diabetic Retinopathy Using Adaptive Boosting And Artificial Neural Network , 2019 .