most citedReal-Time Apple Detection System Using Embedded Systems With Hardware Accelerators: An Edge AI Application

213 citations · 641 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2021★ 2 cited

Domain-Adversarial Training of Self-Attention Based Networks for Land Cover Classification using Multi-temporal Sentinel-2 Satellite Imagery

Mauro Martini, Vittorio Mazzia, Aleem Khaliq +1

The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and c…

eess.IV2020★ 147 cited

Multi-image Super Resolution of Remotely Sensed Images using Residual Feature Attention Deep Neural Networks

Francesco Salvetti, Vittorio Mazzia, Aleem Khaliq +1

Convolutional Neural Networks (CNNs) have been consistently proved state-of-the-art results in image Super-Resolution (SR), representing an exceptional opportunity for the remote s…

cs.CV2020★ 138 cited

Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)

Vittorio Mazzia, Aleem Khaliq, Marcello Chiaberge

The increasing spatial and temporal resolution of globally available satellite images, such as provided by Sentinel-2, creates new possibilities for researchers to use freely avail…

eess.IV2020★ 141 cited

UAV and Machine Learning Based Refinement of a Satellite-Driven Vegetation Index for Precision Agriculture

Vittorio Mazzia, Lorenzo Comba, Aleem Khaliq +2

Precision agriculture is considered to be a fundamental approach in pursuing a low-input, high-efficiency, and sustainable kind of agriculture when performing site-specific managem…

cs.CV2020★ 213 cited

Real-Time Apple Detection System Using Embedded Systems With Hardware Accelerators: An Edge AI Application

Vittorio Mazzia, Francesco Salvetti, Aleem Khaliq +1

Real-time apple detection in orchards is one of the most effective ways of estimating apple yields, which helps in managing apple supplies more effectively. Traditional detection m…