Real-GDSR: Real-World Guided DSM Super-Resolution via Edge-Enhancing Residual Network

A low-resolution digital surface model (DSM) features distinctive attributes impacted by noise, sensor limitations and data acquisition conditions, which failed to be replicated using simple interpolation methods like bicubic. This causes super-resolution models trained on synthetic data does not perform effectively on real ones. Training a model on real low and high resolution DSMs pairs is also a challenge because of the lack of information. On the other hand, the existence of other imaging modalities of the same scene can be used to enrich the information needed for large-scale super-resolution. In this work, we introduce a novel methodology to address the intricacies of real-world DSM super-resolution, named REAL-GDSR, breaking down this ill-posed problem into two steps. The first step involves the utilization of a residual local refinement network. This strategic approach departs from conventional methods that trained to directly predict height values instead of the differences (residuals) and utilize large receptive fields in their networks. The second step introduces a diffusion-based technique that enhances the results on a global scale, with a primary focus on smoothing and edge preservation. Our experiments underscore the effectiveness of the proposed method. We conduct a comprehensive evaluation, comparing it to recent state-of-the-art techniques in the domain of real-world DSM super-resolution (SR). Our approach consistently outperforms these existing methods, as evidenced through qualitative and quantitative assessments.Comment: Accepted for publication in the ISPRS Annals of Photogrammetry, Remote Sensing, and Spatial Information Science

Don't hide in the frames: Note- and pattern-based evaluation of automated melody extraction algorithms

International audienc

Positive FP-CIT SPECT (DaTSCAN) in Clinical Alzheimer's Disease – An Unexpected Finding?

Clinically, Alzheimer's disease (AD) is by far the most common cause of dementia. Criteria for the diagnosis of dementia with Lewy bodies (DLB) are highly specific but not at all sensitive, which is reflected by the higher number of DLB cases detected histopathologically at autopsy. Imaging of dopamine transporter with FP-CIT SPECT is one possibility to increase sensitivity. Pathological confirmation was also included in the revised consensus criteria for the diagnosis of DLB. However, in the absence of parkinsonism, one of the core features, a clinical diagnosis of AD is more likely. The role of FP-CIT SPECT in DLB diagnosis remains to be clarified. Based on our 3 case reports and a review of the literature, the utility of this imaging method in the differential diagnosis of AD and DLB is highlighted

Ultrasonographic Evaluation of Teat Structure and Detection of Prominent Annular Folds in Brazilian Dairy Buffaloes

Udder and teat characteristics differ between buffaloes (Bubalus bubalis) and cattle (Bos taurus) and the differences are important in relation machine milk ability. Dairy buffalo milk out more slowly and are more difficult to milk than dairy cows, especially when milking machines are used. The goal of this study was to determine the ultrasonographic characteristics of udder and teat morphology in dairy buffaloes in Brazil, a country with a relatively recent history of buffalo farming. External assessment of the udder type and ultrasonography of the teat were done in 63 purebred Murrah and Mediterranian x Murrah dairy buffalo cows on three farms with different management systems. Udder types differed among farms; the rear-heavy udder type was most prevalent on two farms and the ball-shaped type occurred frequently on the third farm. Ultrasonographic measurements of the teat were made on one farm and showed correlations between the width of the teat tip and teat canal length, between the width of the teat tip and teat wall thickness and between the width of the teat tip and teat length. During the ultrasonographic examination of the teat, hyperechogenic membrane-like structures in the region of the annular folds, referred to as prominent annular folds (pAFs), were detected in at least one teat in 98 % of all buffaloes. These folds caused narrowing of the lumen between the teat cistern and gland cistern, but their physiological function and relevance concerning machine milk ability remain unclear. Further studies are needed to evaluate the effect of prominent annular folds on milk flow characteristics during mechanical milking in dairy buffaloes

Biomedical Informatics and Granularity

An explicit formal-ontological representation of entities existing at multiple levels of granularity is an urgent requirement for biomedical information processing. We discuss some fundamental principles which can form a basis for such a representation. We also comment on some of the implicit treatments of granularity in currently available ontologies and terminologies (GO, FMA, SNOMED CT)