PhenoBench: A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain

J Weyler, F Magistri, E Marks, YL Chong… - … on Pattern Analysis …, 2024 - ieeexplore.ieee.org
The production of food, feed, fiber, and fuel is a key task of agriculture, which has to cope
with many challenges in the upcoming decades, eg, a higher demand, climate change, lack …

Challenges and opportunities in Machine learning for bioenergy crop yield Prediction: A review

JL Dayil, O Akande, AED Mahmoud, R Kimera… - Sustainable Energy …, 2025 - Elsevier
Bioenergy offers a sustainable alternative to fossil fuels, addressing energy security and
climate change concerns. This paper reviews the current landscape of machine learning …

Robust double-encoder network for rgb-d panoptic segmentation

M Sodano, F Magistri, T Guadagnino… - … on Robotics and …, 2023 - ieeexplore.ieee.org
Perception is crucial for robots that act in real-world environments, as autonomous systems
need to see and understand the world around them to act properly. Panoptic segmentation …

Open-World Semantic Segmentation Including Class Similarity

M Sodano, F Magistri, L Nunes… - Proceedings of the …, 2024 - openaccess.thecvf.com
Interpreting camera data is key for autonomously acting systems such as autonomous
vehicles. Vision systems that operate in real-world environments must be able to understand …

High precision leaf instance segmentation for phenotyping in point clouds obtained under real field conditions

E Marks, M Sodano, F Magistri… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Measuring plant traits with high throughput allows breeders to monitor and select the best
cultivars for subsequent breeding generations. This can enable farmers to improve yield to …

Advances and Challenges in Computer Vision for Image-Based Plant Disease Detection: A Comprehensive Survey of Machine and Deep Learning Approaches

SAA Qadri, NF Huang, TM Wani… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As advancements in agricultural technology unfold, machine learning and deep learning
approaches are gaining interest in robust plant disease identification. Early disease …

OSC-CO2: coattention and cosegmentation framework for plant state change with multiple features

R Quiñones, A Samal, S Das Choudhury… - Frontiers in Plant …, 2023 - frontiersin.org
Cosegmentation and coattention are extensions of traditional segmentation methods aimed
at detecting a common object (or objects) in a group of images. Current cosegmentation and …

Adapting the Segment Anything Model During Usage in Novel Situations

R Schön, J Lorenz, K Ludwig… - Proceedings of the …, 2024 - openaccess.thecvf.com
The interactive segmentation task consists in the creation of object segmentation masks
based on user interactions. The most common way to guide a model towards producing a …

Unsupervised Generation of Labeled Training Images for Crop-Weed Segmentation in New Fields and on Different Robotic Platforms

YL Chong, J Weyler, P Lottes, J Behley… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Agricultural robots have the potential to improve the efficiency and sustainability of existing
agricultural practices. Most autonomous agricultural robots rely on machine vision systems …

High-throughput soybean pods high-quality segmentation and seed-per-pod estimation for soybean plant breeding

S Yang, L Zheng, T Wu, S Sun, M Zhang, M Li… - … Applications of Artificial …, 2024 - Elsevier
Accurately identifying soybean pods is a crucial prerequisite for retrieving multi-phenotypic
traits (such as number of pods per plant, number of seeds per pod, pod size, pod color, and …