Zobrazeno 1 - 10
of 67 322
pro vyhledávání: '"an Dogan"'
Autor:
Oughton, Edward J., Bor, Dennies K., Wiltberger, Michael, Weigel, Robert, Gaunt, C. Trevor, Dogan, Ridvan, Huang, Liling
There is growing concern about our vulnerability to space weather hazards and the disruption critical infrastructure failures could cause to society and the economy. However, the socio-economic impacts of space weather hazards, such as from geomagnet
Externí odkaz:
http://arxiv.org/abs/2412.18032
Creating high-quality 3D avatars using 3D Gaussian Splatting (3DGS) from a monocular video benefits virtual reality and telecommunication applications. However, existing automatic methods exhibit artifacts under novel poses due to limited information
Externí odkaz:
http://arxiv.org/abs/2412.15609
Autor:
Kesgin, H. Toprak, Yuce, M. Kaan, Dogan, Eren, Uzun, M. Egemen, Uz, Atahan, Ince, Elif, Erdem, Yusuf, Shbib, Osama, Zeer, Ahmed, Amasyali, M. Fatih
Publikováno v:
2024 Innovations in Intelligent Systems and Applications Conference (ASYU) published in IEEE Xplore
In this study, we develop and assess new corpus selection and training methodologies to improve the effectiveness of Turkish language models. Specifically, we adapted Large Language Model generated datasets and translated English datasets into Turkis
Externí odkaz:
http://arxiv.org/abs/2412.02775
Autor:
Zeer, Ahmed, Dogan, Eren, Erdem, Yusuf, Ince, Elif, Shbib, Osama, Uzun, M. Egemen, Uz, Atahan, Yuce, M. Kaan, Kesgin, H. Toprak, Amasyali, M. Fatih
In this study, a Turkish visual instruction model was developed and various model architectures and dataset combinations were analysed to improve the performance of this model. The Cosmos-LLaVA model, which is built by combining different large langu
Externí odkaz:
http://arxiv.org/abs/2412.02760
Autor:
Bisson, Tom, O, Isil Dogan, Piwonski, Iris, Kiehl, Tim-Rasmus, Baumgärtner, Georg Lukas, Carvalho, Rita, Hufnagl, Peter, Penzkofer, Tobias, Zerbe, Norman, Elezkurtaj, Sefer
Surgical treatment for prostate cancer often involves organ removal, i.e., prostatectomy. Pathology reports on these specimens convey treatment-relevant information. Beyond these reports, the diagnostic process generates extensive and complex informa
Externí odkaz:
http://arxiv.org/abs/2412.01855
Wikidata has a large ontology with classes at several orders. The Wikidata ontology has long been known to have violations of class order and information related to class order that appears suspect. SPARQL queries were evaluated against Wikidata to d
Externí odkaz:
http://arxiv.org/abs/2411.15550
Multi-modal Representation Learning Enables Accurate Protein Function Prediction in Low-Data Setting
Autor:
Ünsal, Serbülent, Özdemir, Sinem, Kasap, Bünyamin, Kalaycı, M. Erşan, Turhan, Kemal, Doğan, Tunca, Acar, Aybar C.
In this study, we propose HOPER (HOlistic ProtEin Representation), a novel multimodal learning framework designed to enhance protein function prediction (PFP) in low-data settings. The challenge of predicting protein functions is compounded by the li
Externí odkaz:
http://arxiv.org/abs/2412.08649
In most applications, robots need to adapt to new environments and be multi-functional without forgetting previous information. This requirement gains further importance in real-world scenarios where robots operate in coexistence with humans. In thes
Externí odkaz:
http://arxiv.org/abs/2411.05549
Autor:
Flemotomos, Nikolaos, Hsiao, Roger, Swietojanski, Pawel, Hori, Takaaki, Can, Dogan, Zhuang, Xiaodan
Neural contextual biasing allows speech recognition models to leverage contextually relevant information, leading to improved transcription accuracy. However, the biasing mechanism is typically based on a cross-attention module between the audio and
Externí odkaz:
http://arxiv.org/abs/2411.00664
Autor:
Bond, Andrew, Dogan, Zafer
Subspace learning is a critical endeavor in contemporary machine learning, particularly given the vast dimensions of modern datasets. In this study, we delve into the training dynamics of a single-layer GAN model from the perspective of subspace lear
Externí odkaz:
http://arxiv.org/abs/2411.00498