VA
Vani Ashok
Sri Jayachamarajendra College of Engineering
Research areas: Agricultural and Biological Sciences · Plant Science · Smart Agriculture and AI · Industrial Vision Systems and Defect Detection · Spectroscopy and Chemometric Analyses
0000-0002-2064-7464
Employment
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Sri Jayachamarajendra College of Engineering Associate professor
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (18)
- Deep Residual Neural Networks for Protein Structure Prediction Save
- Video Captioning with Text and Audio Output Save
- VisionMate: A Comprehensive Mobile Assistive Application for Visually Impaired Individuals Save
- Enhanced TransUNet for Intracranial Hemorrhage Segmentation: A Superior Approach to Medical Image Segmentation Save
- Generation of Intracranial Hemorrhage CT Scan Images using GAN and VAE Frameworks for Improved Medical Imaging Save
- Hu Moments and transformers: A breakthrough in feature extraction and classification for detecting intracranial hemorrhages in CT scans Save
- Interpretable Machine Learning Approaches for Advancing Disease Prognosis Save
- An Automatic Non-Destructive External and Internal Quality Evaluation of Mango Fruits based on Color and X-ray Imaging using Computer Vision Techniques Save
- Building a Medium Scale Dataset for Non-destructive Disease Classification in Mango Fruits Using Machine Learning and Deep Learning Models Save
- Deep Feature Extraction for EEG Signal Classification in Motor Imagery Tasks Save
- Cephalometric Skeletal Structure Classification Using Convolutional Neural Networks and Heatmap Regression Save
- A Novel Method for Cephalometric Landmark Regression Using Convolutional Neural Networks and Local Binary Pattern Save
- A novel fusion of deep learning and android application for real-time mango fruits disease detection Save
- Diabetic Retinopathy Detection using Retinal Images and Deep Learning Model Save
- Combining Discriminant Analysis and Neural Networks for Detection of Internal Defects in Mangoes using X-Ray Imaging Technique Save
- A comparative study of feature extraction methods in defect classification of mangoes using neural network Save
- Automatic quality evaluation of fruits using Probabilistic Neural Network approach Save
- Using K-means Cluster and Fuzzy C Means for Defect Segmentation in Fruits Save