A5039001509- EEG and Brain-Computer Interfaces
- Smart Agriculture and AI
- Neural and Behavioral Psychology Studies
- Gaze Tracking and Assistive Technology
- Plant Disease Management Techniques
- Plant Virus Research Studies
- Optical Imaging and Spectroscopy Techniques
- Date Palm Research Studies
- Functional Brain Connectivity Studies
- Spectroscopy and Chemometric Analyses
- Mindfulness and Compassion Interventions
- Neuroscience, Education and Cognitive Function
- Human-Automation Interaction and Safety
- Emotion and Mood Recognition
D.Y. Patil University
2023-2024
Ajeenkya DY Patil University
2023-2024
Plant disease detection and early treatment are essential for sustainable crop production. Computer vision science is overgrowing with the advancement in deep learning. Real time plant poses a challenge due to unpredictable spread of diseases within plant, environmental factors, scarcity real field datasets. The proposed work systematically addresses these issues through three key components: (a) Collaboratively generating novel pigeon pea image dataset from agricultural fields, partnership...
The cognitive workload is a key to developing logical and conscious thinking system. Maintaining an optimum improves the performance of individual. individuals' psycho-social factors are responsible for creating significant variability in task, which poses challenge consistent model classification cross-task using physiological signal, Electroencephalogram (EEG). primary focus proposed work develop robust CARNN, by employing concatenated deep structure distributed branches convolutional...
Plant disease detection and early treatment are essential for sustainable crop production. Computer vision science is overgrowing with the advancement in deep learning. However, plant challenging due to random spread throughout body, environmental challenges, lack of actual field datasets. The proposed work systematically addresses these issues with(a) construction first pigeon pea image dataset from agriculture collaboration 20 Agricultural Research Centers (ARS) government agencies across...
The role of emotions in our daily lives is great importance as they have a significant impact on behaviour and interactions with others. Numerous attempts research been undertaken to classify EEG signals for emotion detection. This study presents multi-class classification four emotions, namely happy, sad, neutral, fear, using various classifiers, along 5- 10-folds cross-validation methods. To evaluate which lobe shows the highest accuracy, lobes brain, frontal, temporal, parietal,...