Exploring the potential bioactive compounds group and mechanism of Ci Bai Capsule in treating leukopenia: a combined approach of network pharmacology and transcriptome evidences. [PDF]
Zhang D +8 more
europepmc +1 more source
Identification of Bioactive Peptides from <i>Caenorhabditis elegans</i> Secretions That Promote Indole-3-Acetic Acid Production in <i>Arthrobacter pascens</i> ZZ21. [PDF]
Sun S +7 more
europepmc +1 more source
Precision screening identifies mitoxantrone as a multitarget inhibitor in ageing-associated cancers with extensive computational validation and doxorubicin comparison. [PDF]
Al-Qahtani MH +5 more
europepmc +1 more source
Recent Advances in Raman Spectral Classification with Machine Learning. [PDF]
Liu Y +5 more
europepmc +1 more source
Analyzing the potential of waste cooking oils as biolubricants for electric vehicles. [PDF]
Ayyadevara SN +4 more
europepmc +1 more source
Related searches:
Advanced Automatic Target Recognition (ATR) with Infrared (IR) Sensors
2021 IEEE Aerospace Conference (50100), 2021Automatic Target Detection (ATD) and Recognition (ATR) are critical for video analysis and image understanding for many military and commercial applications deployed on satellites and UAV platforms. Infrared (IR) sensors can be used to detect targets during day and night time but there are few effective ATR algorithms that can exploit these sensors ...
Hai- Wen Chen +4 more
openaire +1 more source
Redefining automatic target recognition (ATR) performance standards
SPIE Proceedings, 2011Present descriptors for Automatic Target Recognition (ATR) performance are inadequate for use in comparing algorithms that are purported to be a solution to the problem. The use of receiver operator characteristic curves (ROCs) is a defacto standard, but they do not communicate several key performance measures, including (i) intrinsic separation ...
Donald Waagen +6 more
openaire +1 more source
A fuzzy hyperspectral classifier for automatic target recognition (ATR) systems
Pattern Recognition Letters, 1999In this paper we present a fuzzy system based hyperspectral classifier for automatic target identification. The system is based on partitioning the spectral band space into clusters using a modified fuzzy C-Means clustering algorithm. Classification of each pixel is then carried out by calculating its fuzzy membership in each cluster.
Sameh M Yamany, Aly A Farag, Shin-Yi Hsu
openaire +1 more source

