8 citations · 27 across the 12 of their papers we have counts for
6 papers · 1 filter
Diffusion-Aided Joint Source Channel Coding For High Realism Wireless Image Transmission
Mingyu Yang, Bowen Liu, Boyang Wang +1
Deep learning-based joint source-channel coding (deep JSCC) has been demonstrated to be an effective approach for wireless image transmission. Nevertheless, most existing work adop…
Siamese Learning-based Monarch Butterfly Localization
Sara Shoouri, Mingyu Yang, Gordy Carichner +7
A new GPS-less, daily localization method is proposed with deep learning sensor fusion that uses daylight intensity and temperature sensor data for Monarch butterfly tracking. Prio…
Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control
Mingyu Yang, Hun-Seok Kim
We present a novel adaptive deep joint source-channel coding (JSCC) scheme for wireless image transmission. The proposed scheme supports multiple rates using a single deep neural n…
OFDM-guided Deep Joint Source Channel Coding for Wireless Multipath Fading Channels
Mingyu Yang, Chenghong Bian, Hun-Seok Kim
We investigate joint source channel coding (JSCC) for wireless image transmission over multipath fading channels. Inspired by recent works on deep learning based JSCC and model-bas…
Deep Joint Source Channel Coding for WirelessImage Transmission with OFDM
Mingyu Yang, Chenghong Bian, Hun-Seok Kim
We present a deep learning based joint source channel coding (JSCC) scheme for wireless image transmission over multipath fading channels with non-linear signal clipping. The propo…
Migrating Monarch Butterfly Localization Using Multi-Sensor Fusion Neural Networks
Mingyu Yang, Roger Hsiao, Gordy Carichner +6
Details of Monarch butterfly migration from the U.S. to Mexico remain a mystery due to lack of a proper localization technology to accurately localize and track butterfly migration…