1 citations · 2 across the 7 of their papers we have counts for
7 papers
RMAU-NET: A Residual-Multihead-Attention U-Net Architecture for Landslide Segmentation and Detection from Remote Sensing Images
Lam Pham, Cam Le, Hieu Tang +6
In recent years, landslide disasters have reported frequently due to the extreme weather events of droughts, floods , storms, or the consequence of human activities such as defores…
Landslide Detection and Segmentation Using Remote Sensing Images and Deep Neural Network
Cam Le, Lam Pham, Jasmin Lampert +2
Knowledge about historic landslide event occurrence is important for supporting disaster risk reduction strategies. Building upon findings from 2022 Landslide4Sense Competition, we…
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms
Lam Pham, Dat Ngo, Cam Le +2
In this technical report, a low-complexity deep learning system for acoustic scene classification (ASC) is presented. The proposed system comprises two main phases: (Phase I) Train…
Deep Learning Based Multimodal with Two-phase Training Strategy for Daily Life Video Classification
Lam Pham, Trang Le, Cam Le +3
In this paper, we present a deep learning based multimodal system for classifying daily life videos. To train the system, we propose a two-phase training strategy. In the first tra…
A Light-weight Deep Learning Model for Remote Sensing Image Classification
Lam Pham, Cam Le, Dat Ngo +4
In this paper, we present a high-performance and light-weight deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the aerial scene of a remo…
A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Classification
Cam Le, Lam Pham, Nghia NVN +2
In this paper, we present a robust and low complexity deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the scene of a remote sensing imag…
Low-complexity deep learning frameworks for acoustic scene classification
Lam Pham, Dat Ngo, Anahid Jalali +1
In this report, we presents low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed frameworks can be separated into four main steps: Front-en…