most citedA Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samples

373 citations · 521 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2021373 cited

A Survey: Deep Learning for Hyperspectral Image Classification with Few Labeled Samples

Sen Jia, Shuguo Jiang, Zhijie Lin +3

With the rapid development of deep learning technology and improvement in computing capability, deep learning has been widely used in the field of hyperspectral image (HSI) classif…

cs.CV202162 cited

A Systematic IoU-Related Method: Beyond Simplified Regression for Better Localization

Hanyang Peng, Shiqi Yu

Four-variable-independent-regression localization losses, such as Smooth- Loss, are used by default in modern detectors. Nevertheless, this kind of loss is oversimplified s…

cs.CV202153 cited

Detect Faces Efficiently: A Survey and Evaluations

Yuantao Feng, Shiqi Yu, Hanyang Peng +2

Face detection is to search all the possible regions for faces in images and locate the faces if there are any. Many applications including face recognition, facial expression reco…

astro-ph.HE202118 cited

Combining Maximum-Likelihood with Deep Learning for Event Reconstruction in IceCube

Mirco Hünnefeld

The field of deep learning has become increasingly important for particle physics experiments, yielding a multitude of advances, predominantly in event classification and reconstru…

astro-ph.HE20215 cited

Reconstructing Neutrino Energy using CNNs for GeV Scale IceCube Events

Jessie Micallef

Measurements of neutrinos at and below 10 GeV provide unique constraints of neutrino oscillation parameters as well as probes of potential Non-Standard Interactions (NSI). The IceC…

astro-ph.HE202110 cited

Study of Mass Composition of Cosmic Rays with IceTop and IceCube

Paras Koundal, Matthias Plum, Julian Saffer

The IceCube Neutrino Observatory is a multi-component detector at the South Pole which detects high-energy particles emerging from astrophysical events. These particles provide us…