Zobrazeno 1 - 10
of 719
pro vyhledávání: '"A, Kasneci"'
Autor:
Kasneci, Gjergji, Kasneci, Enkelejda
Feature engineering is crucial for optimizing machine learning model performance, particularly in tabular data classification tasks. Leveraging advancements in natural language processing, this study presents a systematic approach to enrich tabular d
Externí odkaz:
http://arxiv.org/abs/2411.01645
We introduce to VR a novel imperceptible gaze guidance technique from a recent discovery that human gaze can be attracted to a cue that contrasts from the background in its perceptually non-distinctive ocularity, defined as the relative difference be
Externí odkaz:
http://arxiv.org/abs/2412.09204
Despite the widespread use of LLMs due to their superior performance in various tasks, their high computational costs often lead potential users to opt for the pretraining-finetuning pipeline. However, biases prevalent in manually constructed dataset
Externí odkaz:
http://arxiv.org/abs/2412.07675
Virtual Reality (VR) and Generative Artificial Intelligence (Gen-AI) are transforming personalized learning, particularly in intangible cultural heritage (ICH) education. However, designing immersive experiences that enhance engagement without overwh
Externí odkaz:
http://arxiv.org/abs/2411.18438
The manual assessment and grading of student writing is a time-consuming yet critical task for teachers. Recent developments in generative AI, such as large language models, offer potential solutions to facilitate essay-scoring tasks for teachers. In
Externí odkaz:
http://arxiv.org/abs/2411.16337
Real-time object localization on edge devices is fundamental for numerous applications, ranging from surveillance to industrial automation. Traditional frameworks, such as object detection, segmentation, and keypoint detection, struggle in resource-c
Externí odkaz:
http://arxiv.org/abs/2411.15653
Autor:
Buldu, Kadir Burak, Özdel, Süleyman, Lau, Ka Hei Carrie, Wang, Mengdi, Saad, Daniel, Schönborn, Sofie, Boch, Auxane, Kasneci, Enkelejda, Bozkir, Efe
Recent developments in computer graphics, machine learning, and sensor technologies enable numerous opportunities for extended reality (XR) setups for everyday life, from skills training to entertainment. With large corporations offering consumer-gra
Externí odkaz:
http://arxiv.org/abs/2411.04671
We show how the quality of decisions based on the aggregated opinions of the crowd can be conveniently studied using a sample of individual responses to a standard IQ questionnaire. We aggregated the responses to the IQ questionnaire using simple maj
Externí odkaz:
http://arxiv.org/abs/2410.10004
Autor:
Maquiling, Virmarie, Byrne, Sean Anthony, Niehorster, Diederick C., Carminati, Marco, Kasneci, Enkelejda
We explore the transformative potential of SAM 2, a vision foundation model, in advancing gaze estimation and eye tracking technologies. By significantly reducing annotation time, lowering technical barriers through its ease of deployment, and enhanc
Externí odkaz:
http://arxiv.org/abs/2410.08926
Oral traditions, vital to cultural identity, are losing relevance among youth due to the dominance of modern media. This study addresses the revitalization of these traditions by reconnecting young people with folklore. We introduce Anansi the Spider
Externí odkaz:
http://arxiv.org/abs/2409.16894