Zobrazeno 1 - 10
of 10 105
pro vyhledávání: '"P. Ince"'
Autor:
Kilickaya, Sertac, Ahishali, Mete, Celebioglu, Cansu, Sohrab, Fahad, Eren, Levent, Ince, Turker, Askar, Murat, Gabbouj, Moncef
The frequent breakdowns and malfunctions of industrial equipment have driven increasing interest in utilizing cost-effective and easy-to-deploy sensors, such as microphones, for effective condition monitoring of machinery. Microphones offer a low-cos
Externí odkaz:
http://arxiv.org/abs/2412.10792
The exploration of underwater environments is essential for applications such as biological research, archaeology, and infrastructure maintenanceHowever, underwater imaging is challenging due to the waters unique properties, including scattering, abs
Externí odkaz:
http://arxiv.org/abs/2412.03995
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
Publikováno v:
2023 IEEE International Conference on Robotics and Automation (ICRA) 2023 IEEE International Conference on Robotics and Automation (ICRA) 2024 IEEE International Conference on Robotics and Automation (ICRA)
To operate in open-ended environments where humans interact in complex, diverse ways, autonomous robots must learn to predict their behaviour, especially when that behavior is potentially dangerous to other agents or to the robot. However, reducing t
Externí odkaz:
http://arxiv.org/abs/2407.10639
In this paper, we test the hypothesis that although OpenAI's GPT-4 performs well generally, we can fine-tune open-source models to outperform GPT-4 in smart contract vulnerability detection. We fine-tune two models from Meta's Code Llama and a datase
Externí odkaz:
http://arxiv.org/abs/2407.08969
Autor:
Acikgoz, Emre Can, İnce, Osman Batur, Bench, Rayene, Boz, Arda Anıl, Kesen, İlker, Erdem, Aykut, Erdem, Erkut
The integration of Large Language Models (LLMs) into healthcare promises to transform medical diagnostics, research, and patient care. Yet, the progression of medical LLMs faces obstacles such as complex training requirements, rigorous evaluation dem
Externí odkaz:
http://arxiv.org/abs/2404.16621
Autor:
Yagcioglu, Semih, İnce, Osman Batur, Erdem, Aykut, Erdem, Erkut, Elliott, Desmond, Yuret, Deniz
The rise of large-scale multimodal models has paved the pathway for groundbreaking advances in generative modeling and reasoning, unlocking transformative applications in a variety of complex tasks. However, a pressing question that remains is their
Externí odkaz:
http://arxiv.org/abs/2404.12013
Autor:
Kiranyaz, Serkan, Devecioglu, Ozer Can, Alhams, Amir, Sassi, Sadok, Ince, Turker, Avci, Onur, Gabbouj, Moncef
Robust and real-time detection of faults on rotating machinery has become an ultimate objective for predictive maintenance in various industries. Vibration-based Deep Learning (DL) methodologies have become the de facto standard for bearing fault det
Externí odkaz:
http://arxiv.org/abs/2312.10742
Autor:
İnce, Osman Batur, Zeraati, Tanin, Yagcioglu, Semih, Yaghoobzadeh, Yadollah, Erdem, Erkut, Erdem, Aykut
Neural networks have revolutionized language modeling and excelled in various downstream tasks. However, the extent to which these models achieve compositional generalization comparable to human cognitive abilities remains a topic of debate. While ex
Externí odkaz:
http://arxiv.org/abs/2310.12118