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}ZivaHub2027 · dataset · restricted
Information Filter-based Diffusion Transformer for medical image super-resolutionMedical image super-resolution (SR) aims to recover fine anatomical details from low-resolution (LR) scans, yet obtaining high-resolution images is often challenging due to clinical limitations, such as acquisition time and radiation exposure. To address the limitation of conventional diffusion models with uniform noise perturbation in preserving sparse but clinically important structures, we prop
NCL Data2026 · dataset
Code, split files, out-of-fold predictions and latency measurements for "Coil leakage, training variance and FLOP proxies in the evaluation of real-time steel surface defect detectors"<p dir="ltr">Supplementary material for the article "Coil leakage, training variance and FLOP proxies in the evaluation of real-time steel surface defect detectors" (submitted to the Journal of Real-Time Image Processing).</p><p dir="ltr">The study re-evaluates real-time steel surface defect detectors on NEU-DET and GC10-DET with five-fold cross-validation, coil-disjoint folds for GC10-DET, repeat
Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Crystal structure
Data from: A pilot computer-vision model trained to identify slide-mounted scale insect pests from the family Rhizoecidae<p dir="ltr">Using root mealybugs (Hemiptera: Rhizoecidae) as a test case, this study gathered high-resolution extended depth of field images from slide-mounted museum specimens and trained a convolutional neural network (CNN) to identify and distinguish among 16 species that are encountered as agricultural pests in plant quarantine or greenhouses. A pretrained EfficientNetV2-M model was trained u
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
DySPAM-Net dataset<p dir="ltr">This dataset contains field-collected mango (Mangifera indica L.) canopy images acquired for the development and evaluation of DySPAM-Net (Dynamic Sequential Phenology-Aware Multimodal Network), a deep-learning framework for early-stage mango yield prediction.</p><p dir="ltr">The dataset was collected from a commercial mango orchard in Gujarat, India, using smartphone-based field imag
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
Data and code for: Evaluating Multitask Deep Learning for Multi-Crop Plant Health Recognition under Seed Variation and Crop Transfer<p dir="ltr">This item contains the data records and code supporting the study "Evaluating Multitask Deep Learning for Multi-Crop Plant Health Recognition under Seed Variation and Crop Transfer" (Cogent Food & Agriculture, under review).</p><p dir="ltr">The study compares four output formulations (single-task joint classification, independent multitask heads, multitask fusion, and fusion condition
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
<b>Multimodal Assessment of Historic Building Facades: From Component Core Morphotypes to Building-Level Visible Vulnerability</b><p dir="ltr">该数据集和可重复性包随手稿<b>历史建筑立面检查与建筑层评估的多模态计算》一书。</b> 该研究开发了一种多模态计算工作流程，用于对地理分散的历史建筑立面进行初步检查和建筑层级评估。</p><p dir="ltr">该研究包括<b>220座历史建筑、448张实地照片，以及来自</b>中国东铁路沿线三个研究区的2770个立面构件实例。该工作流程集成了YOLO26m-seg用于组件实例分割，Qwen2.5-VL用于结构化可视化解释，以及基于SAM2的Grounding DINO用于可见光构建和立面测量。</p><p dir="ltr">该库包含补充材料、机器可读统计表、建筑级分析结果、鲁棒性和敏感性分析、空间邻接输出、人工审核统计数据以及研究中使用的可重复性脚本。补充材料包括<b>图S1–S10和表S1–S38</b>，涵盖模型参数、编码粒度分析、立面质量阈值、群集感
ZivaHub + Deakin Research Online + DMU Figshare + UCL Research Data Repository2026 · dataset · unknown
Enhancing gait recognition with 3D markerless motion captureIn recent years gait has increased in popularity as a biometric and gait recognition has matured into a larger field that is is attracting international interest. Most current state-of-the-art gait recognition systems use appearance-based methods which are fast and capable of high performance on gait datasets. With the emergence of deep learning the focus of appearance-based methods has shifted, f
ZivaHub + Deakin Research Online + DMU Figshare + UCL Research Data Repository2026 · dataset · unknown
Deep learning for processing histopathology imagesHistopathology is the study and diagnosis of disease via tissue microscopy and it is currently the ‘gold-standard‘ in formally diagnosing many types of disease including cancers.<br>Due to increasing workloads on pathologists, there is a growing need for automated image analysis pipelines that are able to filter out obviously benign samples. However, these algorithms are sensitive to factors of va
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown
Development of structural assessment approaches for bridges using vision based unmanned aerial systemsThis thesis aims to advance remote sensing techniques for bridge structures using Unmanned Aerial Systems (UAS) to (1) enhance the bridge inspection process particularly for crack detection and (2) to enhance the bridge assessment process by utilising UAS to measure bridge displacements. <br><br>To enhance the bridge inspection process, the study is trying to address the challenges associated with
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
<b>OPAL</b>: A multimodal ambient sensor dataset for activity, occupancy, and energy analysis in an office workspace<p dir="ltr">OPAL (Office Presence, Activity and Load) is a multimodal ambient sensor time-series dataset collected over 33 continuous days in a shared university laboratory workspace at the Gwangju Institute of Science and Technology. Two connected rooms were instrumented: Room 207, the main workspace, and Room 205, a meeting and common area.</p><p dir="ltr">The release combines appliance-level e
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown
Real-time signal processing algorithms for computational millimetre-wave radarsRadar imaging using microwave and millimetre (mmW) frequencies has gained significant popularity for a wide range of applications. The corresponding wavelengths have been proven to successfully penetrate most optically opaque materials and work well in all weather conditions. At the same time, the non-ionizing nature of microwaves and mmW is safe for the human body and has played a significant rol
UCL Research Data Repository2026 · dataset · unknown
A soft coprocessor approach to the development of image and video processing applications on FPGAsDeveloping FPGA-based applications is typically a slow and multi-skilled task. Tools to support application development have gradually become more high level. This thesis describes an approach which aims to raise further the level at which an application developer works while developing FPGA-based implementations of image and video processing applications. <br><br><br>The starting concept is that
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Scour depth prediction, using computer vision at a FlexiArch bridgeScour induced failure of masonry arch bridges is the most common cause of bridge collapse, especially during extreme flood events. Over recent years there has been a significant number of documented scour-induced failures of this bridge stock across the world. The extent of the scour can erode the supporting soil or sediment around the bridge piers or abutments, leading to a loss of support for th
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown
Deep learning of dyadic interaction visual cues for human-robot collaboration in assembly tasks<p></p><p>This thesis examines the integration of multiple visual cues in dyadic interactions through deep learning to improve interactivity and intuitiveness in human-robot interactions, particularly in assembly tasks. Serving as a preliminary effort, these bodies of work seek to address the critical deficiencies in current dyadic human robot interaction methodologies, which typically depend on i
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown
Super-resolution in millimetre-wave compressive computational imagingImaging at millimetre wave (mmW) has many advantages over infrared (IR), X-ray and optical imaging. MmWs can penetrate through materials that are opaque at optical wavelengths. They do not possess any ionizing effects, and hence are harmless to human exposure. They can also be operated in all weather conditions, making them suitable for both indoor and outdoor use. Because of all these advantages,
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset · unknown
FPGA-based programmable embedded platform for image processing applicationsA vast majority of electronic systems including medical, surveillance and critical infrastructure employs image processing to provide intelligent analysis. They use onboard pre-processing to reduce data bandwidth and memory requirements before sending information to the central system. Field Programmable Gate Arrays (FPGAs) represent a strong platform as they permit reconfigurability and pipelinin
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Alternative 3D processing techniques for complex automated material handlingThis project presents a new method for applying classical image processing and morphology to 3D vision systems. The motivation for this project is to allow for the further development of Autonomous Guided Vehicles (AGVs), specifically in their ability to interact with complex objects that cannot be characterised by current learning data sets, placed in un-structured environments. Current trends in
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
<b>Code for "A model-fitting perspective on the robustness and speed of CLASS in reflection matrix microscopy"</b><p dir="ltr">Python implementation of the pupil-phase solvers compared in the accompanying paper, <b>"A model-fitting perspective on the robustness and speed of CLASS in reflection matrix microscopy"</b>, together with the experiment runners that reproduce Figures 3 to 6 and the scripts that compose those figures.</p><p dir="ltr">The paper recasts CLASS as the solution of a model-fitting problem a
Teesside University Research Data Repository2026 · dataset · unknown
CLBP-400: A Real-World Video Dataset for Cuff-Less Blood Pressure Estimation via rPPGThe development of remote blood pressure (BP) measurement algorithms using remote photoplethysmography (rPPG) has significant limitations, including the small size of publicly available datasets, privacy concerns regarding facial videos, and a lack of diverse, realistic datasets associated with actual BP measurements. To address these challenges, this study aimed to provide comprehensive, simultan
ZivaHub + Deakin Research Online + DMU Figshare + UCL Research Data Repository2026 · Crystal structure · unknown
Development of hybrid rotomoulded composite structuresRotational moulding is a manufacturing process that produces huge hollow plastic parts compared to injection or blow moulding. In a typical rotomoulding cycle, a polymer powder is loaded into a metal mould to be bi-axially rotated and heated. Once a molten plastic layer entirely covers the mould, the tool is moved to a cooling chamber where the temperature decreases until the part is solidified to
UCL Research Data Repository2026 · dataset · unknown
Development of a time-synchronised multi-input computer vision system for structural monitioring utilising deep learning for vehicle identificationA reliable transport infrastructure is vital to the commercial and lifestyle demands of a developed country, with the majority of journeys occurring by road. Bridges are a key component of this infrastructure, if a bridge fails or is unnecessarily closed it has widespread adverse effects throughout the surrounding area. Detailed monitoring is essential to ensure adequate maintenance of these struct
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Microfracture Evolution and Transformation Mechanism of Coal Induced by Supercritical Carbon Dioxide Fracturing under True Triaxial Stress ConditionsSupercritical carbon dioxide (ScCO<sub>2</sub>) fracturing is an important stimulation technology for enhancing coalbed methane production, and microfracture evolution directly affects the seepage capacity of coal reservoirs. To reveal the evolution and transformation mechanism of ScCO<sub>2</sub>-induced microfractures under true triaxial stress conditions, fracturing experiments were conducted u
ZivaHub + Deakin Research Online + DMU Figshare2026 · dataset
Цифровизация нефтегазовой отрасли: Как компьютерные технологии меняют добычу и переработку углеводородов<p dir="ltr">· <b>Цифровой двойник месторождения:</b> Компьютерная система создаёт виртуальную копию всей инфраструктуры — от отдельной скважины до магистрального трубопровода. Это позволяет виртуально тестировать различные сценарии эксплуатации без риска для реального оборудования.</p>
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
Visualization1.aviRotating-object measurement
ZivaHub + Deakin Research Online + DMU Figshare + HKU DataHub + Swinburne Figshare + DaYta Ya Rona + SUNScholarData + figshare + Loughborough Research Repository + GRANTS Data + UP Research Data Repository2026 · Astronomical catalogue
3D In-Air Signature Dataset<p dir="ltr">This dataset contains 3D in-air hand signatures collected using the Leap Motion Controller 2. It includes annotated CSV files for 65 users, with 10 signature instances per user (total 650 instances). The data captures finger, palm, and arm positions, velocities, rotations, etc. making it suitable for Intermittent Spatial Segmentation research. It can be extended for In-Air Signature v