Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 4 of 4 for “"Hybrid CNN"”.
-
REPRESENTATION LEARNING FOR VISUAL TASKS: A STUDY OF ATTENTION AND INFORMATION SELECTION
… research utilizes Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and Graph Neural Networks (GNNs) and targets improvements in image classification (single and multi-label) and fine-grained image retrieval. Four primary contributions are detailed: (1) CNN2Graph, a hybrid CNN-GNN …
-
A Context Aware Classification System for Monitoring Driver’s Distraction Levels
… Recurrent Convolutional Neural Network (Fast-RCNN) architecture addresses the physiological attributes. Secondly, a novel two-tier FRCNN-LSTM framework is devised to classify the severity of driver distraction. Thirdly, a Dynamic Bayesian Network (DBN) for the prediction of driver distraction. …
-
Data driven modeling and MPC Based control for Pathological Tremors
… frequency composition as the actual tremor. 2 hybrid CNN-LSTM based deep learning architectures are then proposed to predict the tremor kinematics ahead of time using EMG signals and tremor kinematics history, and the results are compared with baseline models. This is then further extended by …
-
Object Detection Using Vision Transformed EfficientDet
… particularly convolutional neural networks (CNNs), have significantly improved the accuracy and efficiency of computer vision systems. Object detection, a widely studied application within computer vision, involves the identification and localization of objects in images. The ViT backbone, …