Tat-Jun Chin

Towards fully neuromorphic star tracking for spacecraft jitter mitigation

Ashwin Subramaniam, Linh Co Bui, Tat-Jun Chin, William S. P. Robertson et autres

au (code pays fourni par la source)

Robust PnP on a Neuromorphic Processor for Object Pose Estimation

Tam Ngoc-Bang Nguyen, Mohsi Jawaid, Tat-Jun Chin

Neuromorphic computing is gaining attention in robotic perception due to its higher energy efficiency. While neural network-based methods can more readily exploit the distributed and parallelized structure of neuromorphic computers, crafting neuromorphic solutions for non-learning tasks is less straightforward. This hampers the …

Robust PnP on a Neuromorphic Processor for Object Pose Estimation

Tam Ngoc-Bang Nguyen, Mohsi Jawaid, Tat-Jun Chin

Neuromorphic computing is gaining attention in robotic perception due to its higher energy efficiency. While neural network-based methods can more readily exploit the distributed and parallelized structure of neuromorphic computers, crafting neuromorphic solutions for non-learning tasks is less straightforward. This hampers the …

Uncertainty-Guided Edge Learning for Deep Image Regression in Remote Sensing

Anh Ngoc Nguyen, Dino Sejdinović, Tat-Jun Chin

Edge learning refers to training machine learning models deployed on edge platforms, typically using new data accumulated onboard. The computational limitations on edge devices affect not only model optimisation, but also calculation of the predictive uncertainty of the current model on the …

Uncertainty-Guided Edge Learning for Deep Image Regression in Remote Sensing

Anh Vu Nguyen, Dino Sejdinović, Tat-Jun Chin

Edge learning refers to training machine learning models deployed on edge platforms, typically using new data accumulated onboard. The computational limitations on edge devices affect not only model optimisation, but also calculation of the predictive uncertainty of the current model on the …

au (code pays fourni par la source)

AI-enabled crater-based navigation for lunar mapping

Sofia McLeod, Chee-Kheng Chng, Matthew Rodda, Tat-Jun Chin

Abstract Crater-based navigation (CBN) uses the ubiquitous impact craters of the Moon observed on images as natural landmarks to determine the six degrees of freedom (6Dof) pose of a spacecraft. To date, CBN has primarily been studied in the context of powered …

au (code pays fourni par la source)

SceneEdited: A City-Scale Benchmark for 3D HD Map Updating via Image-Guided Change Detection

Chun-Jung Lin, Tat-Jun Chin, Sourav Garg, Feras Dayoub

au (code pays fourni par la source)

MoBind: Motion Binding for Fine-Grained IMU-Video Pose Alignment

Duc Duy Nguyen, Tat-Jun Chin, Minh Hoai

We aim to learn a joint representation between inertial measurement unit (IMU) signals and 2D pose sequences extracted from video, enabling accurate cross-modal retrieval, temporal synchronization, subject and body-part localization, and action recognition. To this end, we introduce MoBind, a hierarchical contrastive …

MoBind: Motion Binding for Fine-Grained IMU-Video Pose Alignment

Duc Duy Nguyen, Tat-Jun Chin, Minh Hoai

We aim to learn a joint representation between inertial measurement unit (IMU) signals and 2D pose sequences extracted from video, enabling accurate cross-modal retrieval, temporal synchronization, subject and body-part localization, and action recognition. To this end, we introduce MoBind, a hierarchical contrastive …

High-Throughput Event-Based Feature Detection and Tracking on an Embedded CPU

Ethan Elms, Yasir Latif, Tat-Jun Chin

au (code pays fourni par la source)

First On-Orbit Demonstration of a Geospatial Foundation Model

Andrew Du, Roberto Del Prete, Alejandro Mousist, Nick Manser et autres

Geospatial foundation models (GeoFMs) promise broad generalisation capacity for Earth observation (EO) tasks, particularly under data-limited conditions. However, their large size poses a barrier to deployment on resource-constrained space hardware. To address this, we present compact variants of a Vision Transformer (ViT)-based …

Finding Outliers in a Haystack: Anomaly Detection for Large Pointcloud Scenes

Ryan Faulkner, Luke Haub, Simon Ratcliffe, Tat-Jun Chin

au (code pays fourni par la source)