Single image dehazing has received a lot of concern and achieved great success with the help of deep-learning models. Yet, the performance is limited by the local limitation of convolution. To address such a limitation, we design a novel deep learning de
In PISTE, the conventional, data-driven attention mechanism is replaced with physics-driven dynamics that steers the positioning of amino acid residues along the gradient field of their interactions. This allows navigating the intricate landscape of biosequence interactions intelligently, leading to ...
The ongoing progress in MLFF development has resulted in a wide range of increasingly sophisticated model architectures aiming to improve the extrapolation behavior. Among these, message passing neural networks (MPNNs)9,12,34have emerged as a particularly effective class of architectures. MPNNs can be ...
2021, Journal of Physics Communications Survey on High-Temperature Superconducting Transformer Windings Design 2020, Journal of Superconductivity and Novel Magnetism An effective way to reduce AC loss of second-generation high temperature superconductors ...
The objective extends beyond merely recalibrating the weights of the positive and negative samples; it encompasses the nuanced regulation of weights assigned to samples that are challenging to classify as well as those that are readily classifiable. In the course of training, the lane-edge proposal...
Problems involving geometric data arise in physics, chemistry, robotics, computer vision, and many other fields. Such data can take numerous forms, such as points, direction vectors, translations, or rotations, but to date there is no single architecture that can be applied to such a wide varie...
Specifically, we use 12 different scales ranging from 32 to 384 pixels and 3 aspect ratios (0.5, 1.0, 1.5) to define a total of 36 anchors. We then project all 3D ground truth boxes to the 2D space and calculate its intersection over union (IoU) with each 2D anchor and assign the ...
Department of Physics, College of Arts, Science and Education, Florida International University, Miami, FL, USA Prabin Baral & Prem Chapagain Biomolecular Sciences Institute, Florida International University, Miami, FL, USA Prem Chapagain, Kalai Mathee & Giri Narasimhan ...
Notably, the performance was stably improved the same as in the experiments without adding these other class data (Fig. 5a), suggesting the robustness of the proposed framework to assure that the AI model is not confused by these unseen classes to the initial model trained only with normal ...
Computational protein-binding studies are widely used to investigate fundamental biological processes and facilitate the development of modern drugs, vaccines and therapeutics. Scoring functions aim to assess and rank the binding strength of the predicte