Search Results for author: Richard O. Sinnott

Found 7 papers, 1 papers with code

Autonomous Vehicle Patrolling Through Deep Reinforcement Learning: Learning to Communicate and Cooperate

no code implementations28 Jan 2024 Chenhao Tong, Maria A. Rodriguez, Richard O. Sinnott

However, an optimal coordination strategy is often non-trivial to be manually defined due to the complex nature of patrolling environments.

Autonomous Vehicles Collision Avoidance +1

Improved Knowledge Distillation for Crowd Counting on IoT Device

1 code implementation IEEE International Conference on Edge Computing and Communications 2023 Zuo Huang, Richard O. Sinnott

This is comparable to state-of-the-art deep crowd counting models, but at a fraction of the original model size and complexity, thus making the solution suitable for IoT devices.

Crowd Counting Knowledge Distillation +1

Fake News Detection Through Graph-based Neural Networks: A Survey

no code implementations24 Jul 2023 Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi, Cecile Paris

In recent years, graph-based methods have yielded strong results, as they can closely model the social context and propagation process of online news.

Fake News Detection Misinformation

Machine Learning-based Classification of Birds through Birdsong

no code implementations9 Dec 2022 Yueying Chang, Richard O. Sinnott

Audio sound recognition and classification is used for many tasks and applications including human voice recognition, music recognition and audio tagging.

Audio Tagging Classification

A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks

no code implementations14 Jun 2022 Zihan Yang, Richard O. Sinnott, James Bailey, Qiuhong Ke

To mitigate such problem, a novel direction is to automatically learn the image augmentation policies from the given dataset using Automated Data Augmentation (AutoDA) techniques.

Image Augmentation Image Classification

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