4 papers
A Catalog of Giant Radio Source Candidates from TGSS ADR1 Using a Deep Learning--based Pipeline
Baoqiang Lao, Binghua Liang, Shaoguang Guo +4
We present a catalog of 5,595 giant radio source (GRS) candidates, defined by a largest (projected) linear size (LLS) exceeding 0.7 Mpc. Of these, 4,566 would be new discoveries if…
A Catalog of 971 FR-I Radio Galaxies from the FIRST Survey via Hybrid Deep Learning and Ridgeline Flux Density Distribution Analysis
Baoqiang Lao, Xiaolong Yang, Wenjun Xiao +6
We present a catalog of 971 FR-I radio galaxies (FR-Is) identified from the Very Large Array Faint Images of the Radio Sky at Twenty-Centimeters (FIRST) survey. The identifications…
Identifying Quasi-Periodic Micropulses in Pulsars with FAST Using Convolutional Neural Networks
Shidong Wang, Hui Liu, Ru-Shuang Zhao +12
Quasi-periodic MicroPulses (QMP) are quasi-periodic microstructural features manifested in individual pulsar radio pulses, the study of which is crucial for understanding pulsar ra…
Identification of 4876 Bent-Tail Radio Galaxies in the FIRST Survey Using Deep Learning Combined with Visual Inspection
Baoqiang Lao, Heinz Andernach, Xiaolong Yang +6
Bent-tail radio galaxies (BTRGs) are characterized by bent radio lobes. This unique shape is mainly caused by the movement of the galaxy within a cluster, during which the radio je…