research
∙
06/01/2023
LiT-4-RSVQA: Lightweight Transformer-based Visual Question Answering in Remote Sensing
Visual question answering (VQA) methods in remote sensing (RS) aim to an...
share
research
∙
10/10/2022
Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensing
With the new generation of satellite technologies, the archives of remot...
research
∙
10/05/2022
Advanced Deep Learning Architectures for Accurate Detection of Subsurface Tile Drainage Pipes from Remote Sensing Images
Subsurface tile drainage pipes provide agronomic, economic and environme...
research
∙
07/28/2022
On the Effects of Different Types of Label Noise in Multi-Label Remote Sensing Image Classification
The development of accurate methods for multi-label classification (MLC)...
research
∙
04/19/2022
Unsupervised Contrastive Hashing for Cross-Modal Retrieval in Remote Sensing
The development of cross-modal retrieval systems that can search and ret...
research
∙
02/26/2022
An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote Sensing
The development of accurate and scalable cross-modal image-text retrieva...
research
∙
01/20/2022
Deep Unsupervised Contrastive Hashing for Large-Scale Cross-Modal Text-Image Retrieval in Remote Sensing
Due to the availability of large-scale multi-modal data (e.g., satellite...
research
∙
05/12/2021
A Novel Uncertainty-aware Collaborative Learning Method for Remote Sensing Image Classification Under Multi-Label Noise
In remote sensing (RS), collecting a large number of reliable training i...
research
∙
05/08/2021
A Novel Triplet Sampling Method for Multi-Label Remote Sensing Image Search and Retrieval
Learning the similarity between remote sensing (RS) images forms the fou...
research
∙
12/19/2020
CCML: A Novel Collaborative Learning Model for Classification of Remote Sensing Images with Noisy Multi-Labels
The development of accurate methods for multi-label classification (MLC)...
research
∙
04/09/2019
Generative Models for Novelty Detection: Applications in abnormal event and situational change detection from data series
Novelty detection is a process for distinguishing the observations that ...
research
∙
06/08/2018
Hierarchy of GANs for learning embodied self-awareness model
In recent years several architectures have been proposed to learn embodi...
research
∙
06/07/2018
Learning Multi-Modal Self-Awareness Models for Autonomous Vehicles from Human Driving
This paper presents a novel approach for learning self-awareness models ...
research
∙
03/17/2018
A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents
This paper focuses on multi-sensor anomaly detection for moving cognitiv...
research
∙
08/31/2017
Abnormal Event Detection in Videos using Generative Adversarial Nets
In this paper we address the abnormality detection problem in crowded sc...
research
∙
06/23/2017
Training Adversarial Discriminators for Cross-channel Abnormal Event Detection in Crowds
Abnormal crowd behaviour detection attracts a large interest due to its ...
research
∙
11/21/2016
Efficient Convolutional Neural Network with Binary Quantization Layer
In this paper we introduce a novel method for segmentation that can bene...
research
∙
10/02/2016
Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection
Most of the crowd abnormal event detection methods rely on complex hand-...
research
∙
09/29/2016
CNN-aware Binary Map for General Semantic Segmentation
In this paper we introduce a novel method for general semantic segmentat...
research
∙
12/13/2015