2 citations · 4 across the 5 of their papers we have counts for
5 papers · 1 filter
From Words to Wavelengths: VLMs for Few-Shot Multispectral Object Detection
Manuel Nkegoum, Minh-Tan Pham, Élisa Fromont +2
Multispectral object detection is critical for safety-sensitive applications such as autonomous driving and surveillance, where robust perception under diverse illumination conditi…
FSMODNet: A Closer Look at Few-Shot Detection in Multispectral Data
Manuel Nkegoum, Minh-Tan Pham, Élisa Fromont +2
Few-shot multispectral object detection (FSMOD) addresses the challenge of detecting objects across visible and thermal modalities with minimal annotated data. In this paper, we ex…
Contributions to Label-Efficient Learning in Computer Vision and Remote Sensing
Minh-Tan Pham
This manuscript presents a series of my selected contributions to the topic of label-efficient learning in computer vision and remote sensing. The central focus of this research is…
HVT: A Comprehensive Vision Framework for Learning in Non-Euclidean Space
Jacob Fein-Ashley, Ethan Feng, Minh Pham
Data representation in non-Euclidean spaces has proven effective for capturing hierarchical and complex relationships in real-world datasets. Hyperbolic spaces, in particular, prov…
Variational Autoencoder for Anomaly Detection: A Comparative Study
Huy Hoang Nguyen, Cuong Nhat Nguyen, Xuan Tung Dao +3
This paper aims to conduct a comparative analysis of contemporary Variational Autoencoder (VAE) architectures employed in anomaly detection, elucidating their performance and behav…