A Framework for Predictive Modeling in Sustainable Projects حسب Labban, Tarek

احصل على النص الكامل

Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network حسب Monzure-Khoda Kazi (17191207)

"…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …"

Fine-grain watermarking for intellectual property protection حسب Stefano Giovanni Rizzo (18615112)

"…The core method is based on homoglyph characters substitution for latin symbols and whitespaces. …"

Optimal Trajectory and Positioning of UAVs for Small Cell HetNets: Geometrical Analysis and Reinforcement Learning Approach حسب Mohammad Taghi Dabiri (16904658)

"…Then, using geometrical analysis and deep reinforcement learning (RL) method, we propose several algorithms to find the optimal trajectory and select an optimal pattern during the trajectory. …"

Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging حسب Maricar, Mohammed Farook

احصل على النص الكامل

Multimodal feature fusion and ensemble learning for non-intrusive occupancy monitoring using smart meters حسب Sakib Mahmud (15302404)

"…We combine features from all three modes of MMF-NIOM to achieve a state-of-the-art non-intrusive occupancy classification performance of 91.5 % accuracy and 91.5 % f1-score, approximately, by an ensemble of fine-tuned classifiers on the electricity consumption & occupancy (ECO) dataset. The proposed method is sustainable, robust, adaptable to various households, and can be mass-implemented within smart meters at a much lower cost and effort compared to the traditional internet of things (IoT)-based intrusive systems.…"

Con-Detect: Detecting adversarially perturbed natural language inputs to deep classifiers through holistic analysis حسب Hassan, Ali

"…We thus propose Con-Detect—a Contribution based Detection method—for detecting adversarial attacks against NLP classifiers. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

Con-Detect: Detecting Adversarially Perturbed Natural Language Inputs to Deep Classifiers Through Holistic Analysis حسب Hassan Ali (3348749)

"…We thus propose Con-Detect—a Contribution based Detection method—for detecting adversarial attacks against NLP classifiers. …"