Search Results for author: Mingyu Yang

Found 16 papers, 12 papers with code

Diving with Penguins: Detecting Penguins and their Prey in Animal-borne Underwater Videos via Deep Learning

1 code implementation14 Aug 2023 Kejia Zhang, Mingyu Yang, Stephen D. J. Lang, Alistair M. McInnes, Richard B. Sherley, Tilo Burghardt

In this paper, we publish an animal-borne underwater video dataset of penguins and introduce a ready-to-deploy deep learning system capable of robustly detecting penguins (mAP50@98. 0%) and also instances of fish (mAP50@73. 3%).

Siamese Learning-based Monarch Butterfly Localization

no code implementations4 Jul 2023 Sara Shoouri, Mingyu Yang, Gordy Carichner, Yuyang Li, Ehab A. Hamed, Angela Deng, Delbert A. Green II, Inhee Lee, David Blaauw, Hun-Seok Kim

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.

Sensor Fusion

Efficient Computation Sharing for Multi-Task Visual Scene Understanding

1 code implementation ICCV 2023 Sara Shoouri, Mingyu Yang, Zichen Fan, Hun-Seok Kim

Solving multiple visual tasks using individual models can be resource-intensive, while multi-task learning can conserve resources by sharing knowledge across different tasks.

Multi-Task Learning Scene Understanding

NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

2 code implementations17 Jun 2022 Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui

First, GNNs can learn higher-order structural information by stacking more layers but can not deal with large depth due to the over-smoothing issue.

Graph Representation Learning Link Prediction +1

Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality Selection

1 code implementation12 May 2022 Mingyu Yang, Yu Chen, Hun-Seok Kim

In recent years, deep learning-based approaches for visual-inertial odometry (VIO) have shown remarkable performance outperforming traditional geometric methods.

Pose Estimation

Multi-Target Active Object Tracking with Monte Carlo Tree Search and Target Motion Modeling

no code implementations7 May 2022 Zheng Chen, Jian Zhao, Mingyu Yang, Wengang Zhou, Houqiang Li

In this work, we are dedicated to multi-target active object tracking (AOT), where there are multiple targets as well as multiple cameras in the environment.

Multi-agent Reinforcement Learning Object Tracking

LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning

no code implementations5 May 2022 Mingyu Yang, Jian Zhao, Xunhan Hu, Wengang Zhou, Jiangcheng Zhu, Houqiang Li

In this way, agents dealing with the same subtask share their learning of specific abilities and different subtasks correspond to different specific abilities.

Multi-agent Reinforcement Learning reinforcement-learning +3

CTDS: Centralized Teacher with Decentralized Student for Multi-Agent Reinforcement Learning

1 code implementation16 Mar 2022 Jian Zhao, Xunhan Hu, Mingyu Yang, Wengang Zhou, Jiangcheng Zhu, Houqiang Li

In this way, CTDS balances the full utilization of global observation during training and the feasibility of decentralized execution for online inference.

Multi-agent Reinforcement Learning reinforcement-learning +3

Deep Joint Source-Channel Coding for Wireless Image Transmission with Adaptive Rate Control

1 code implementation9 Oct 2021 Mingyu Yang, Hun-Seok Kim

To the best of our knowledge, this is the first deep JSCC scheme that can automatically adjust its rate using a single network model.

OFDM-guided Deep Joint Source Channel Coding for Wireless Multipath Fading Channels

1 code implementation11 Sep 2021 Mingyu Yang, Chenghong Bian, Hun-Seok Kim

We investigate joint source channel coding (JSCC) for wireless image transmission over multipath fading channels.

Deep Joint Source Channel Coding for WirelessImage Transmission with OFDM

2 code implementations5 Jan 2021 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.

BIG-bench Machine Learning

Migrating Monarch Butterfly Localization Using Multi-Sensor Fusion Neural Networks

no code implementations14 Dec 2019 Mingyu Yang, Roger Hsiao, Gordy Carichner, Katherine Ernst, Jaechan Lim, Delbert A. Green II, Inhee Lee, David Blaauw, Hun-Seok Kim

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.

Sensor Fusion

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