Zobrazeno 1 - 10
of 7 985
pro vyhledávání: '"Roberts, Michael"'
Autor:
Oruganti, Sanjay, Nirenburg, Sergei, McShane, Marjorie, English, Jesse, Roberts, Michael K., Arndt, Christian
This paper presents a novel approach to multi-robot planning and collaboration. We demonstrate a cognitive strategy for robots in human-robot teams that incorporates metacognition, natural language communication, and explainability. The system is emb
Externí odkaz:
http://arxiv.org/abs/2409.18047
Autor:
Oruganti, Sanjay, Nirenburg, Sergei, McShane, Marjorie, English, Jesse, Roberts, Michael K., Arndt, Christian
We present HARMONIC, a framework for implementing cognitive robots that transforms general-purpose robots into trusted teammates capable of complex decision-making, natural communication and human-level explanation. The framework supports interoperab
Externí odkaz:
http://arxiv.org/abs/2409.18037
Autor:
Deltadahl, Simon, Gilbey, Julian, Van Laer, Christine, Boeckx, Nancy, Leers, Mathie, Freeman, Tanya, Aiken, Laura, Farren, Timothy, Smith, Matthew, Zeina, Mohamad, consortium, BloodCounts!, Piazzese, Concetta, Taylor, Joseph, Gleadall, Nicholas, Schönlieb, Carola-Bibiane, Sivapalaratnam, Suthesh, Roberts, Michael, Nachev, Parashkev
Accurate classification of haematological cells is critical for diagnosing blood disorders, but presents significant challenges for machine automation owing to the complexity of cell morphology, heterogeneities of biological, pathological, and imagin
Externí odkaz:
http://arxiv.org/abs/2408.08982
Autor:
Breger, Anna, Karner, Clemens, Selby, Ian, Gröhl, Janek, Dittmer, Sören, Lilley, Edward, Babar, Judith, Beckford, Jake, Else, Thomas R, Sadler, Timothy J, Shahipasand, Shahab, Thavakumar, Arthikkaa, Roberts, Michael, Schönlieb, Carola-Bibiane
Image quality assessment (IQA) is standard practice in the development stage of novel machine learning algorithms that operate on images. The most commonly used IQA measures have been developed and tested for natural images, but not in the medical se
Externí odkaz:
http://arxiv.org/abs/2405.19224
Autor:
Breger, Anna, Biguri, Ander, Landman, Malena Sabaté, Selby, Ian, Amberg, Nicole, Brunner, Elisabeth, Gröhl, Janek, Hatamikia, Sepideh, Karner, Clemens, Ning, Lipeng, Dittmer, Sören, Roberts, Michael, Collaboration, AIX-COVNET, Schönlieb, Carola-Bibiane
Image quality assessment (IQA) is not just indispensable in clinical practice to ensure high standards, but also in the development stage of novel algorithms that operate on medical images with reference data. This paper provides a structured and com
Externí odkaz:
http://arxiv.org/abs/2405.19097
Autor:
Zhang, Fan, Esteve-Yagüe, Carlos, Dittmer, Sören, Schönlieb, Carola-Bibiane, Roberts, Michael
Federated Learning (FL) enables collaborative training of machine learning models on decentralized data while preserving data privacy. However, data across clients often differs significantly due to class imbalance, feature distribution skew, sample
Externí odkaz:
http://arxiv.org/abs/2405.19000
Autor:
Zheng, Rangrang, Schivley, Greg, Hidalgo-Gonzalez, Patricia, Fripp, Matthias, Roberts, Michael J.
Solar and wind power are cost-competitive with fossil fuels, yet their intermittent nature presents challenges. Significant temporal and geographic differences in land, wind, and solar resources suggest that long-distance transmission could be partic
Externí odkaz:
http://arxiv.org/abs/2402.14189
Whilst the size and complexity of ML models have rapidly and significantly increased over the past decade, the methods for assessing their performance have not kept pace. In particular, among the many potential performance metrics, the ML community s
Externí odkaz:
http://arxiv.org/abs/2312.16188