Domain Generalization for Crop Segmentation with Knowledge Distillation

In recent years, precision agriculture has gradually oriented farming closer to automation processes to support all the activities related to field management. Service robotics plays a predominant role in this evolution by deploying autonomous agents that can navigate fields while performing tasks without human intervention, such as monitoring, spraying, and harvesting. To execute these precise actions, mobile robots need a real-time perception system that understands their surroundings and identifies their targets in the wild. Generalizing to new crops and environmental conditions is critical for practical applications, as labeled samples are rarely available. In this paper, we investigate the problem of crop segmentation and propose a novel approach to enhance domain generalization using knowledge distillation. In the proposed framework, we transfer knowledge from an ensemble of models individually trained on source domains to a student model that can adapt to unseen target domains. To evaluate the proposed method, we present a synthetic multi-domain dataset for crop segmentation containing plants of variegate shapes and covering different terrain styles, weather conditions, and light scenarios for more than 50,000 samples. We demonstrate significant improvements in performance over state-of-the-art methods and superior sim-to-real generalization. Our approach provides a promising solution for domain generalization in crop segmentation and has the potential to enhance a wide variety of precision agriculture applications

Autonomous Navigation in Rows of Trees and High Crops with Deep Semantic Segmentation

Segmentation-based autonomous navigation has recently been proposed as a promising methodology to guide robotic platforms through crop rows without requiring precise GPS localization. However, existing methods are limited to scenarios where the centre of the row can be identified thanks to the sharp distinction between the plants and the sky. However, GPS signal obstruction mainly occurs in the case of tall, dense vegetation, such as high tree rows and orchards. In this work, we extend the segmentation-based robotic guidance to those scenarios where canopies and branches occlude the sky and hinder the usage of GPS and previous methods, increasing the overall robustness and adaptability of the control algorithm. Extensive experimentation on several realistic simulated tree fields and vineyards demonstrates the competitive advantages of the proposed solution

Lavender Autonomous Navigation with Semantic Segmentation at the Edge

Achieving success in agricultural activities heavily relies on precise navigation in row crop fields. Recently, segmentation-based navigation has emerged as a reliable technique when GPS-based localization is unavailable or higher accuracy is needed due to vegetation or unfavorable weather conditions. It also comes in handy when plants are growing rapidly and require an online adaptation of the navigation algorithm. This work applies a segmentation-based visual agnostic navigation algorithm to lavender fields, considering both simulation and real-world scenarios. The effectiveness of this approach is validated through a wide set of experimental tests, which show the capability of the proposed solution to generalize over different scenarios and provide highly-reliable results

Productivity changes in the Mediterranean Sea drive foraging movements of yelkouan shearwater Puffinus yelkouan from the core of its global breeding range

Pelagic seabirds are tied to their breeding colonies throughout their long-lasting breeding season, but at the same time, they have to feed in a highly dynamic marine environment where prey abundance and availability rapidly change across space and seasons. Here, we describe the foraging movements of yelkouan shearwater Puffinus yelkouan, a seabird endemic to the Mediterranean Sea that spends its entire life cycle within this enclosed basin and whose future conservation is intimately linked to human-driven and climatic changes affecting the sea. The aim was to understand the main factors underlying the choice of foraging locations during the reproductive phases. A total of 34 foraging trips were obtained from 21 breeding adults tagged and tracked on Tavolara Archipelago (N Sardinia, Italy). This is the largest and most important breeding area for the species, accounting for more than 50% of the world population. The relationships between foraging movements during two different breeding stages and the seasonal changes of primary productivity at sea were modeled. Movements appeared to be addressed toward inshore (<20 km), highly productive, and relatively shallow (<200 m) foraging areas, often in front of river mouths and at great distances from the colony. During incubation, the Bonifacio Strait and other coastal areas close to North and West Sardinia were the most preferred locations (up to 247 km from the colony). During the chick-rearing phase, some individuals reached areas placed at greater distances from the colony (up to 579 km), aiming at food-rich hotspots placed as far north as the Gulf of Lion (France). The need for such long distance and long-lasting foraging trips is hypothesized to be related to unfavorable conditions on the less productive (and already depleted) Sardinian waters

Potential use of human adipose mesenchymal stromal cells for intervertebral disc regeneration: a preliminary study on biglycan-deficient murine model of chronic disc degeneration

INTRODUCTION: Biglycan is an important proteoglycan of the extracellular matrix of intervertebral disc (IVD), and its decrease with aging has been correlated with IVD degeneration. Biglycan deficient (Bgn(−/0)) mice lack this protein and undergo spontaneous IVD degeneration with aging, thus representing a valuable in vivo model for preliminary studies on therapies for human progressive IVD degeneration. The purpose of the present study was to assess the possible beneficial effects of adipose-derived stromal cells (ADSCs) implants in the Bgn(−/0) mouse model. METHODS: To evaluate ADSC implant efficacy, Bgn(−/0) mice were intradiscally (L1-L2) injected with 8x10(4) ADSCs at 16 months old, when mice exhibit severe and complete IVD degeneration, evident on both 7Tesla Magnetic Resonance Imaging (7TMRI) and histology. Placebo and ADSCs treated Bgn(−/0) mice were assessed by 7TMRI analysis up to 12 weeks post-transplantation. Mice were then sacrificed and implanted discs were analyzed by histology and immunohistochemistry for the presence of human cells and for the expression of biglycan and aggrecan in the IVD area. RESULTS: After in vivo treatment, 7TMRI revealed evident increase in signal intensity within the discs of mice that received ADSCs, while placebo treatment did not show any variation. Ultrastructural analyses demonstrated that human ADSC survival occurred in the injected discs up to 12 weeks after implant. These cells acquired a positive expression for biglycan, and this proteoglycan was specifically localized in human cells. Moreover, ADSC treatment resulted in a significant increase of aggrecan tissue levels. CONCLUSION: Overall, this work demonstrates that ADSC implant into degenerated disc of Bgn(−/0) mice ameliorates disc damage, promotes new expression of biglycan and increased levels of aggrecan. This suggests a potential benefit of ADSC implant in the treatment of chronic degenerative disc disease and prompts further studies in this field

Preservation of modern and MIS 5.5 erosional landforms and biological structures as sea level markers : a matter of luck?

The Mediterranean Basin is characterized by a significant variability in tectonic behaviour, ranging from subsidence to uplifting. However, those coastal areas considered to be tectonically stable show coastal landforms at elevations consistent with eustatic and isostatic sea level change models. In particular, geomorphological indicators—such as tidal notches or shore platforms—are often used to define the tectonic stability of the Mediterranean coasts. We present the results of swim surveys in nine rocky coastal sectors in the central Mediterranean Sea using the Geoswim approach. The entire route was covered in 22 days for a total distance of 158.5 km. All surveyed sites are considered to have been tectonically stable since the last interglacial (Marine Isotope Stage 5.5 [MIS 5.5]), because related sea level markers fit well with sea level rise models. The analysis of visual observations and punctual measurements highlighted that, with respect to the total length of surveyed coast, the occurrence of tidal notches, shore platforms, and other indicators accounts for 85% of the modern coastline, and only 1% of the MIS 5.5 equivalent. Therefore, only 1% of the surveyed coast showed the presence of fossil markers of paleo sea levels above the datum. This significant difference is mainly attributable to erosion processes that did not allow the preservation of the geomorphic evidence of past sea level stands. In the end, our research method showed that the feasibility of applying such markers to define long-term tectonic behaviour is much higher in areas where pre-modern indicators have not been erased, such as at sites with hard bedrock previously covered by post-MIS 5.5 continental deposits, e.g., Sardinia, the Egadi Islands, Ansedonia, Gaeta, and Circeo. In general, the chances of finding such preserved indicators are very low.peer-reviewe

Autonomous Navigation in Rows of Trees and High Crops with Deep Semantic Segmentation

Segmentation-based autonomous navigation has recently been proposed as a promising methodology to guide robotic platforms through crop rows without requiring precise GPS localization. However, existing methods are limited to scenarios where the centre of the row can be identified thanks to the sharp distinction between the plants and the sky. However, GPS signal obstruction mainly occurs in the case of tall, dense vegetation, such as high tree rows and orchards. In this work, we extend the segmentation-based robotic guidance to those scenarios where canopies and branches occlude the sky and hinder the usage of GPS and previous methods, increasing the overall robustness and adaptability of the control algorithm. Extensive experimentation on several realistic simulated tree fields and vineyards demonstrates the competitive advantages of the proposed solution

X-ray Micro-Tomography as a Method to Distinguish and Characterize Natural and Cultivated Pearls

Digital radiography and computed tomography are two fundamental diagnostic techniques in different fields of research, including cultural heritage studies and gemmology. The application of these physical methods of investigation has gained considerable importance as they are non-invasive techniques. The presented work has been mainly focused on micro-tomographic analysis. The project is concerned with the study of natural and cultivated pearls in order to develop an investigation methodology for the analysis, distinction and characterization of different types of pearls, some of them belonging to different precious jewels from private collections. The investigations, carried out on a total of 22 heterogeneous types of pearls, allowed us to establish their origin (natural or cultivated) or to confirm/deny if a hypothesis was already expressed, and as well to highlight the cultivation methodology used case by case. Furthermore, it was possible to ascertain how large and varied the market for cultured pearls is nowadays and how difficult is, in some particular cases, to ascertain their attribution to a certain origin