leo-plese/artificial-intelligence-machine-learning-deep-learning/computer-vision/graduate-diploma-thesis-project/dense-prediction-by-means-of-self-attention-layers

Dense Prediction by Means of Self-attention Layers - research of models for dense prediction (semantic segmentation) - primarily transformers (models in focus: Segmenter, Swin transformer) and comparison with convolutional models (model in focus: pyramidal SwiftNet). Also, research, design and implementation of pyramidal models of transformer-convolutional model (Segmenter-SwiftNet) and transformer-transformer (Segmenter-Segmenter) type. Implementation is in PyTorch deep learning framework. My graduate thesis computer vision project.

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leo-plese/artificial-intelligence-machine-learning-deep-learning/computer-vision/graduate-diploma-thesis-project/swin-transformer-models-for-semantic-segmentation

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leo-plese/artificial-intelligence-machine-learning-deep-learning/computer-vision/graduate-diploma-thesis-project/segmenter-transformer-models-for-semantic-segmentation

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leo-plese/artificial-intelligence-machine-learning-deep-learning/computer-vision/graduate-diploma-thesis-project/swiftnet-convolutional-models-with-pyramidal-fusion-for-semantic-segmentation

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