Results 261 to 270 of about 7,324,417 (308)

Using cell‐free RNA to identify B‐ and T‐cell clonality for diagnosis and monitoring of B‐ and T‐cell neoplasms

FEBS Open Bio, EarlyView.
Using peripheral blood for determining B‐cell or T‐cell clonality is more reliable when we use cell‐free RNA (cfRNA) because cells release blood significantly more RNA than DNA. Next‐generation sequencing (NGS) of cfRNA allows us to evaluate fragment cfRNA and evaluate clonality reliably without the need for prior determination of the specific dominant
Adam Albitar, Sally Agersborg, Ahmed Charifa, Pooja Phull, Noa Biran, David Vesole, Harsh Parmar, Andrew Pecora, Andrew Ip, Andre Goy, David Siegel, Maher Albitar   +11 more
wiley   +1 more source

FasterGeo-YOLO: Multi-Scale Geometric Adaptive Feature Enhancement for Lightweight Road Damage Detection. [PDF]

Sensors (Basel)
Zhang L, Yang R, Qin Z, Lu Y, Zhang B, He S, Jin Y.   +6 more
europepmc   +1 more source

Development of Loop-Mediated Isothermal Amplification Assays for Rapid and Sensitive Detection of Three Viruses Infecting <i>Areca catechu</i> L. [PDF]

Plants (Basel)
Niu X, Tian Y, Shen J, Zhu H, Gao F.
europepmc   +1 more source

EMamba: A MoE-enhanced state space network for robust steel surface defect detection. [PDF]

PLoS One
Yang H, Wang P, Liu Y.
europepmc   +1 more source

TCCA: An Inter-Layer Spatiotemporal Cross-Attention Network for IIoT Attack Traffic Detection. [PDF]

Sensors (Basel)
Sun X, Xu B.
europepmc   +1 more source

REW-DETR: A Lightweight Real-Time Detection Transformer for Bridge Surface Defect Detection. [PDF]

Sensors (Basel)
Cheng X, Pang Y, Wang Y, Deng Y, Lu Q.
europepmc   +1 more source

YOLO-Based Vision Perception and Automation for Agricultural Robots: A Comprehensive Survey of Algorithms, Applications, and Deployment. [PDF]

Sensors (Basel)
Ping H, Zhang Z, Song C, Ping T.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Computationally efficient face detection

Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2002
This paper describes an algorithm for finding faces within an image. The basis of the algorithm is to run an observation window at all possible positions, scales and orientation within the image. A non-linear support vector machine is used to determine whether or not a face is contained within the observation window.
Romdhani, S, Torr, P, Schölkopf, B, Blake, A   +3 more
openaire   +4 more sources