Essays about: "computer thesis networks"
Showing result 16 - 20 of 330 essays containing the words computer thesis networks.
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16. Introducing GA-SSNN: A Method for Optimizing Stochastic Spiking Neural Networks : Scaling the Edge User Allocation Constraint Satisfaction Problem with Enhanced Energy and Time Efficiency
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : As progress within Von Neumann-based computer architecture is being limited by the physical limits of transistor size, neuromorphic comuting has emerged as a promising area of research. Neuromorphic hardware tends to be substantially more power efficient by imitating the aspects of computations in networks of neurons in the brain. READ MORE
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17. Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : Neuromorphic processors are a promising new type of hardware for optimizing neural network computation using biologically-inspired principles. They can effectively leverage information sparsity such as in images from event-based cameras, and are well-adapted to processing event-based data in an energy-efficient fashion. READ MORE
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18. Real-time uncertainty estimation for deep learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Modern deep neural networks do not produce well calibrated estimates of their own uncertainty, unless specific uncertainty estimation techniques are applied. Common uncertainty estimation techniques such as Deep Ensembles and Monte Carlo Dropout necessitate multiple forward pass evaluations for each input sample, making them too slow for real-time use. READ MORE
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19. A Comparison of CNN and Transformer in Continual Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Within the realm of computer vision tasks, Convolutional Neural Networks (CNN) and Transformers represent two predominant methodologies, often subject to extensive comparative analyses elucidating their respective merits and demerits. This thesis embarks on an exploration of these two models within the framework of continual learning, with a specific focus on their propensities for resisting catastrophic forgetting. READ MORE
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20. Fog detection using an artificial neural network
University essay from Lunds universitet/Matematisk statistikAbstract : This project studies a method of image-based fog detection directly from a camera without using the transmissometer. Fog can be detected using transmissometers which could be a very costly approach. This thesis presents an image-based approach for fog detection using Artificial Neural networks. READ MORE
