78 citations · 207 across the 11 of their papers we have counts for
8 papers · 1 filter
Self-Supervised Data Generation for Precision Agriculture: Blending Simulated Environments with Real Imagery
Leonardo Saraceni, Ionut Marian Motoi, Daniele Nardi +1
In precision agriculture, the scarcity of labeled data and significant covariate shifts pose unique challenges for training machine learning models. This scarcity is particularly p…
Synthetic Data Generation for Anomaly Detection on Table Grapes
Ionut Marian Motoi, Valerio Belli, Alberto Carpineto +2
Early detection of illnesses and pest infestations in fruit cultivation is critical for maintaining yield quality and plant health. Computer vision and robotics are increasingly em…
Can Robots "Taste" Grapes? Estimating SSC with Simple RGB Sensors
Thomas Alessandro Ciarfuglia, Ionut Marian Motoi, Leonardo Saraceni +1
In table grape cultivation, harvesting depends on accurately assessing fruit quality. While some characteristics, like color, are visible, others, such as Soluble Solid Content (SS…
Evaluating the Efficacy of Cut-and-Paste Data Augmentation in Semantic Segmentation for Satellite Imagery
Ionut M. Motoi, Leonardo Saraceni, Daniele Nardi +1
Satellite imagery is crucial for tasks like environmental monitoring and urban planning. Typically, it relies on semantic segmentation or Land Use Land Cover (LULC) classification…
AgriSORT: A Simple Online Real-time Tracking-by-Detection framework for robotics in precision agriculture
Leonardo Saraceni, Ionut M. Motoi, Daniele Nardi +1
The problem of multi-object tracking (MOT) consists in detecting and tracking all the objects in a video sequence while keeping a unique identifier for each object. It is a challen…
Weakly and Semi-Supervised Detection, Segmentation and Tracking of Table Grapes with Limited and Noisy Data
Thomas A. Ciarfuglia, Ionut M. Motoi, Leonardo Saraceni +3
Detection, segmentation and tracking of fruits and vegetables are three fundamental tasks for precision agriculture, enabling robotic harvesting and yield estimation applications.…
The Role of the Input in Natural Language Video Description
Silvia Cascianelli, Gabriele Costante, Alessandro Devo +3
Natural Language Video Description (NLVD) has recently received strong interest in the Computer Vision, Natural Language Processing (NLP), Multimedia, and Autonomous Robotics commu…
LS-VO: Learning Dense Optical Subspace for Robust Visual Odometry Estimation
Gabriele Costante, Thomas A. Ciarfuglia
This work proposes a novel deep network architecture to solve the camera Ego-Motion estimation problem. A motion estimation network generally learns features similar to Optical Flo…