Viral News

ISLES 2024: The first longitudinal multimodal multi-center real-world dataset in (sub-)acute stroke
23 Aug

ISLES 2024: The first longitudinal multimodal multi-center real-world dataset in (sub-)acute stroke

stp2y0 CommentsViral News
[Submitted on 20 Aug 2024] Authors:Evamaria O. Riedel, Ezequiel de la Rosa, The Anh Baran, Moritz Hernandez Petzsche, Hakim Baazaoui, Kaiyuan Yang, David Robben, Joaquin Oscar Seia, Roland Wiest, Mauricio Reyes, Ruisheng Su, Claus Zimmer, Tobias Boeckh-Behrens, Maria Berndt, Bjoern Menze, Benedikt Wiestler, Susanne Wegener, Jan S. Kirschke View a PDF of the paper titled ISLES 2024: The first longitudinal multimodal multi-center real-world dataset in (sub-)acute stroke, by Evamaria O. Riedel and 17 other authors View PDF Abstract:Stroke remains a leading cause of global morbidity and mortality, placing a heavy socioeconomic burden. Over the past decade, advances in endovascular reperfusion…
Read More
OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs
23 Aug

OpenFactCheck: A Unified Framework for Factuality Evaluation of LLMs

stp2y0 CommentsViral News
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol
Read More
Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function
23 Aug

Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function

stp2y0 CommentsViral News
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol
Read More
Binocular Model: A deep learning solution for online melt pool temperature analysis using dual-wavelength Imaging Pyrometry
23 Aug

Binocular Model: A deep learning solution for online melt pool temperature analysis using dual-wavelength Imaging Pyrometry

stp2y0 CommentsViral News
arXiv:2408.11126v1 Announce Type: new Abstract: In metal Additive Manufacturing (AM), monitoring the temperature of the Melt Pool (MP) is crucial for ensuring part quality, process stability, defect prevention, and overall process optimization. Traditional methods, are slow to converge and require extensive manual effort to translate data into actionable insights, rendering them impractical for real-time monitoring and control. To address this challenge, we propose an Artificial Intelligence (AI)-based solution aimed at reducing manual data processing reliance and improving the efficiency of transitioning from data to insight. In our study, we utilize a dataset comprising dual-wavelength real-time process monitoring data and corresponding…
Read More
The Mechanics of Conceptual Interpretation in GPT Models: Interpretative Insights
23 Aug

The Mechanics of Conceptual Interpretation in GPT Models: Interpretative Insights

stp2y0 CommentsViral News
arXiv:2408.11827v1 Announce Type: new Abstract: Locating and editing knowledge in large language models (LLMs) is crucial for enhancing their accuracy, safety, and inference rationale. We introduce ``concept editing'', an innovative variation of knowledge editing that uncovers conceptualisation mechanisms within these models. Using the reverse dictionary task, inference tracing, and input abstraction, we analyse the Multi-Layer Perceptron (MLP), Multi-Head Attention (MHA), and hidden state components of transformer models. Our results reveal distinct patterns: MLP layers employ key-value retrieval mechanism and context-dependent processing, which are highly associated with relative input tokens. MHA layers demonstrate a distributed nature with significant higher-level activations, suggesting…
Read More
MicroXercise: A Micro-Level Comparative and Explainable System for Remote Physical Therapy
23 Aug

MicroXercise: A Micro-Level Comparative and Explainable System for Remote Physical Therapy

stp2y0 CommentsViral News
[Submitted on 6 Aug 2024] View a PDF of the paper titled MicroXercise: A Micro-Level Comparative and Explainable System for Remote Physical Therapy, by Hanchen David Wang and 5 other authors View PDF HTML (experimental) Abstract:Recent global estimates suggest that as many as 2.41 billion individuals have health conditions that would benefit from rehabilitation services. Home-based Physical Therapy (PT) faces significant challenges in providing interactive feedback and meaningful observation for therapists and patients. To fill this gap, we present MicroXercise, which integrates micro-motion analysis with wearable sensors, providing therapists and patients with a comprehensive feedback interface, including video, text, and…
Read More
GSLoc: Efficient Camera Pose Refinement via 3D Gaussian Splatting
23 Aug

GSLoc: Efficient Camera Pose Refinement via 3D Gaussian Splatting

stp2y0 CommentsViral News
arXiv:2408.11085v1 Announce Type: new Abstract: We leverage 3D Gaussian Splatting (3DGS) as a scene representation and propose a novel test-time camera pose refinement framework, GSLoc. This framework enhances the localization accuracy of state-of-the-art absolute pose regression and scene coordinate regression methods. The 3DGS model renders high-quality synthetic images and depth maps to facilitate the establishment of 2D-3D correspondences. GSLoc obviates the need for training feature extractors or descriptors by operating directly on RGB images, utilizing the 3D vision foundation model, MASt3R, for precise 2D matching. To improve the robustness of our model in challenging outdoor environments, we incorporate an exposure-adaptive…
Read More
Unboxing Occupational Bias: Grounded Debiasing LLMs with U.S. Labor Data
23 Aug

Unboxing Occupational Bias: Grounded Debiasing LLMs with U.S. Labor Data

stp2y0 CommentsViral News
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol
Read More
Total Uncertainty Quantification in Inverse PDE Solutions Obtained with Reduced-Order Deep Learning Surrogate Models
23 Aug

Total Uncertainty Quantification in Inverse PDE Solutions Obtained with Reduced-Order Deep Learning Surrogate Models

stp2y0 CommentsViral News
[Submitted on 20 Aug 2024] View a PDF of the paper titled Total Uncertainty Quantification in Inverse PDE Solutions Obtained with Reduced-Order Deep Learning Surrogate Models, by Yuanzhe Wang and Alexandre M. Tartakovsky View PDF HTML (experimental) Abstract:We propose an approximate Bayesian method for quantifying the total uncertainty in inverse PDE solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations and PDE and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then,…
Read More
BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition
23 Aug

BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition

stp2y0 CommentsViral News
[Submitted on 20 Aug 2024] View a PDF of the paper titled BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition, by Md Hadiuzzaman and 5 other authors View PDF HTML (experimental) Abstract:People commonly communicate in English, Arabic, and Bengali spoken languages through various mediums. However, deaf and hard-of-hearing individuals primarily use body language and sign language to express their needs and achieve independence. Sign language research is burgeoning to enhance communication with the deaf community. While many researchers have made strides in recognizing sign languages such as French, British, Arabic, Turkish, and American, there has…
Read More
No widgets found. Go to Widget page and add the widget in Offcanvas Sidebar Widget Area.