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20082022
most citedUnsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images

216 citations · 426 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.CV2021

An Enhanced Randomly Initialized Convolutional Neural Network for Columnar Cactus Recognition in Unmanned Aerial Vehicle Imagery

Safa Ben Atitallah, Maha Driss, Wadii Boulila +3

Recently, Convolutional Neural Networks (CNNs) have made a great performance for remote sensing image classification. Plant recognition using CNNs is one of the active deep learnin…

cs.CV2020

Deep-Learning-based Automated Palm Tree Counting and Geolocation in Large Farms from Aerial Geotagged Images

Adel Ammar, Anis Koubaa

In this paper, we propose a deep learning framework for the automated counting and geolocation of palm trees from aerial images using convolutional neural networks. For this purpos…

cs.CV20205 cited

DriftNet: Aggressive Driving Behavior Classification using 3D EfficientNet Architecture

Alam Noor, Bilel Benjdira, Adel Ammar +1

Aggressive driving (i.e., car drifting) is a dangerous behavior that puts human safety and life into a significant risk. This behavior is considered as an anomaly concerning the re…

cs.CV2019

Activity Monitoring of Islamic Prayer (Salat) Postures using Deep Learning

Anis Koubaa, Adel Ammar, Bilel Benjdira +6

In the Muslim community, the prayer (i.e. Salat) is the second pillar of Islam, and it is the most essential and fundamental worshiping activity that believers have to perform five…

cs.CV2019

AI-based Pilgrim Detection using Convolutional Neural Networks

Marwa Ben Jabra, Adel Ammar, Anis Koubaa +2

Pilgrimage represents the most important Islamic religious gathering in the world where millions of pilgrims visit the holy places of Makkah and Madinah to perform their rituals. T…

cs.CV2019216 cited

Unsupervised Domain Adaptation using Generative Adversarial Networks for Semantic Segmentation of Aerial Images

Bilel Benjdira, Yakoub Bazi, Anis Koubaa +1

Segmenting aerial images is being of great potential in surveillance and scene understanding of urban areas. It provides a mean for automatic reporting of the different events that…