Essays about: "Adversarial machine learning"

Showing result 1 - 5 of 107 essays containing the words Adversarial machine learning.

1. 1. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance

   University essay from Uppsala universitet/Avdelningen för beräkningsvetenskap

   Author : Stella Jarlöv; Anton Svensson Dahl; [2023]
   Keywords : demand forecasting; data augmentation; time series data; machine learning; restaurant industry; generative adversarial networks; TimeGAN; XGBoost;

   Abstract : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. READ MORE

3. 2. Using Synthetic Data to ModelMobile User Interface Interactions

   University essay from Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Author : Laoa Jalal; [2023]
   Keywords : Time Series Data; Generative Adversarial Networks; Synthetic Data Generator; Usability Testing; Machine Learning;

   Abstract : Usability testing within User Interface (UI) is a central part of assuring high-quality UIdesign that provides good user-experiences across multiple user-groups. The processof usability testing often times requires extensive collection of user feedback, preferablyacross multiple user groups, to ensure an unbiased observation of the potential designflaws within the UI design. READ MORE

4. 3. Adversarial robustness of STDP-trained spiking neural networks

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Karl Lindblad; Axel Nilsson; [2023]
   Keywords : ;

   Abstract : Adversarial attacks on machine learning models are designed to elicit the wrong behavior from the model. One such attack on image classifiers are maliciously crafted inputs that, to the human eye, look untampered with but have been carefully altered to cause misclassification. READ MORE

5. 4. Adversarial Machine (Deep) Learning-basedRobustification in 5G Networks

   University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Author : Mirjalol Aminov; [2023]
   Keywords : 5G; Network Slicing; Adversarial Machine Learning; Machine Learning; Deep Learning;

   Abstract :  A significant development in wireless communication and artificial intelligence has been made possible by the combination of 5G networks with deep learning methods. This paper explores the complex interactions between these areas, concentrating on the dangers that adversarial attacks represent in the context of 5G network slicing. READ MORE

6. 5. Using Generative Adversarial Networks for H&E-to-HER2 Stain Translation in Digital Pathology Images

   University essay from Linköpings universitet/Institutionen för medicinsk teknik

   Author : William Tirmén; [2023]
   Keywords : Machine learning; Artificial intelligence; Digital pathology; Image processing; Generative adversarial networks; Image-to-image translation;

   Abstract : In digital pathology, hematoxylin & eosin (H&E) is a routine stain which is performed on most clinical cases and it often provides clinicians with sufficient information for diagnosis. However, when making decisions on how to guide breast cancer treatment, immunohistochemical staining of human epidermal growth factor 2 (HER2 staining) is also needed. READ MORE