A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education حسب Abu Zitar, Raed

"…Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. …"
احصل على النص الكامل

Barriers of Adopting Artificial Intelligence Tools in Engineering Construction Projects حسب ALKAABI, ABDULLA

"…Finally, interoperability and integration issues may hinder AI adoption. Incorporating AI into pre-existing software, systems, and processes may require significant effort and tailoring, and compatibility issues may hinder the easy integration of AI utilities into building projects.…"
احصل على النص الكامل

Large language models for code completion: A systematic literature review حسب Rasha Ahmad Husein (19744756)

"…<p>Code completion serves as a fundamental aspect of modern software development, improving developers' coding processes. Integrating code completion tools into an Integrated Development Environment (IDE) or code editor enhances the coding process and boosts productivity by reducing errors and speeding up code writing while reducing cognitive load. …"

Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort حسب Sergio Márquez-Sánchez (19437985)

"…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …"

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

"…Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …"
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)

"…<p>Deep Learning (DL) algorithms have shown wonders in many Natural Language Processing (NLP) tasks such as language-to-language translation, spam filtering, fake-news detection, and comprehension understanding. …"