activity
20222024
most citedIntegrating Features for Recognizing Human Activities through Optimized Parameters in Graph Convolutional Networks and Transformer Architectures

1 citations · 4 across the 10 of their papers we have counts for

collaborators

10 papers

cs.RO20241 cited

An Aerial Transport System in Marine GNSS-Denied Environment

Jianjun Sun, Zhenwei Niu, Yihao Dong +6

This paper presents an autonomous aerial system specifically engineered for operation in challenging marine GNSS-denied environments, aimed at transporting small cargo from a targe…

cs.RO2024

A Comprehensive Review of Current Robot- Based Pollinators in Greenhouse Farming

Rajmeet Singh, lakmal Seneviratne, Irfan Hussain

The decline of bee and wind-based pollination systems in greenhouses due to controlled environments and limited access has boost the importance of finding alternative pollination m…

cs.CV20241 cited

Integrating Features for Recognizing Human Activities through Optimized Parameters in Graph Convolutional Networks and Transformer Architectures

Mohammad Belal, Taimur Hassan, Abdelfatah Hassan +3

Human activity recognition is a major field of study that employs computer vision, machine vision, and deep learning techniques to categorize human actions. The field of deep learn…

cs.RO2024

Long-Range Vision-Based UAV-assisted Localization for Unmanned Surface Vehicles

Waseem Akram, Siyuan Yang, Hailiang Kuang +7

The global positioning system (GPS) has become an indispensable navigation method for field operations with unmanned surface vehicles (USVs) in marine environments. However, GPS ma…

cs.CV2024

Feature Fusion for Human Activity Recognition using Parameter-Optimized Multi-Stage Graph Convolutional Network and Transformer Models

Mohammad Belal, Taimur Hassan, Abdelfatah Ahmed +3

Human activity recognition (HAR) is a crucial area of research that involves understanding human movements using computer and machine vision technology. Deep learning has emerged a…

cs.RO20241 cited

Object Manipulation in Marine Environments using Reinforcement Learning

Ahmed Nader, Muhayy Ud Din, Mughni Irfan +1

Performing intervention tasks in the maritime domain is crucial for safety and operational efficiency. The unpredictable and dynamic marine environment makes the intervention tasks…