Results 91 to 100 of about 788,437 (264)
Image Outpainting: Hallucinating Beyond the Image
IEEE Access, 2020 Image inpainting is a technique that aims to fill in the missing regions with visually plausible content. However, an opposite idea, which is painting outside images, receives little work.
Qingguo Xiao +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Liquid biopsy enables minimally invasive, real‐time molecular profiling through analysis of circulating biomarkers in biological fluids. This Perspective highlights the importance of training pathologists through integrative educational programs, such as the European Masters in Molecular Pathology, to ensure effective and equitable implementation of ...
Marius Ilié +13 more
wiley +1 more source
CREST: Convolutional Residual Learning for Visual Tracking
, 2017 Discriminative correlation filters (DCFs) have been shown to perform superiorly in visual tracking. They only need a small set of training samples from the initial frame to generate an appearance model. However, existing DCFs learn the filters separately
Gong, Lijun +5 more
core +1 more source
MoRe-ERL: Learning Motion Residuals Using Episodic Reinforcement Learning
IEEE Robotics and Automation LettersWe propose MoRe-ERL, a framework that combines Episodic Reinforcement Learning (ERL) and residual learning, which refines preplanned reference trajectories into safe, feasible, and efficient task-specific trajectories. This framework is general enough to incorporate into arbitrary ERL methods and motion generators seamlessly.
Xi Huang +7 more
openaire +2 more sources
Next‐generation proteomics improves lung cancer risk prediction
Molecular Oncology, EarlyView.This is one of very few studies that used prediagnostic blood samples from participants of two large population‐based cohorts. We identified, evaluated, and validated an innovative protein marker model that outperformed an established risk prediction model and criteria employed by low‐dose computed tomography in lung cancer screening trials.
Megha Bhardwaj +4 more
wiley +1 more source
Dictionary Learning of Convolved Signals [PDF]
, 2013 Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation of them.
Barchiesi, Daniele, Plumbley, Mark
core +1 more source
Demystifying Deep Learning: A Geometric Approach to Iterative Projections
, 2018 Parametric approaches to Learning, such as deep learning (DL), are highly popular in nonlinear regression, in spite of their extremely difficult training with their increasing complexity (e.g. number of layers in DL).
Dai, Liyi, Krim, Hamid, Panahi, Ashkan
core +1 more source
Residual-NeRF: Learning Residual NeRFs for Transparent Object Manipulation
2024 IEEE International Conference on Robotics and Automation (ICRA)Transparent objects are ubiquitous in industry, pharmaceuticals, and households. Grasping and manipulating these objects is a significant challenge for robots. Existing methods have difficulty reconstructing complete depth maps for challenging transparent objects, leaving holes in the depth reconstruction.
Duisterhof, Bardienus P. +3 more
openaire +2 more sources
Molecular Oncology, EarlyView.The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg +43 more
wiley +1 more source
Molecular Oncology, EarlyView.This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris +10 more
wiley +1 more source