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- Heikki A. KalviainenSuggested from co-authorship
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Works176 from public data
- the DIARETDB1 diabetic retinopathy database and evaluation protocol921
With the proposed database and protocol, it is possible to compare different algorithms, and correspondingly, analyse their maturity for technology transfer from the research laboratories to the medical practice.
- Differential Evolution Training Algorithm for Feed-Forward Neural Networks639
In this study, differential evolution has been analyzed as a candidate global optimization method for feed-forward neural networks and seems not to provide any distinct advantage in terms of learning rate or solution quality.
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- The Eighth Visual Object Tracking VOT2020 Challenge Results350
A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in theVDT challenges.
- AR-based interaction for human-robot collaborative manufacturing252
A depth-sensor based model for workspace monitoring and an interactive Augmented Reality (AR) User Interface (UI) for safe HRC are proposed and evaluated in a realistic diesel engine assembly task.
- Simple Gabor feature space for invariant object recognition220
In this study, fundamental properties of Gabor features, construction of the simple feature space, and invariant search operations in the feature space are discussed in more detail.
- Feature representation and discrimination based on Gaussian mixture model probability densities—Practices and algorithms182
In this study maximum likelihood estimation methods for Gaussian mixture models are reviewed and discussed from a practical point of view, and good practices for utilizing probability densities in feature classification and selection are discussed for Bayesian and for non-Bayesian tasks.
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- DepthTrack: Unveiling the Power of RGBD Tracking130
A new RGBD tracking dataset - Depth-Track - is introduced that has twice as many sequences and scene types than in the largest existing dataset, and three times more objects, and the average length of the sequences, number of deformable objects and the number of annotated tracking attributes have been increased.
- The Ninth Visual Object Tracking VOT2021 Challenge Results127
The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative; results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years.
- Object Detection in Equirectangular Panorama114
A high-resolution equirectangular panorama dataset for object detection and a multi-projection variant of the YOLO detector, which outperforms the other state-of-the-art detector, Faster R-CNN, and achieves the best accuracy with low-resolution input.
- Object Tracking by Reconstruction With View-Specific Discriminative Correlation Filters98
The proposed long-term RGB-D tracker called OTR – Object Tracking by Reconstruction performs online 3D target reconstruction to facilitate robust learning of a set of view-specific discriminative correlation filters (DCFs).
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- On Finding Gray Pixels85
The grayness index, GI in short, is derived using the Dichromatic Reflection Model and is learning-free, and outperforms state-of-the-art statistical methods and many recent deep methods.
- CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark83
The CDTB dataset is the largest and most diverse dataset in RGB-D tracking, with an order of magnitude larger number of frames than related datasets, indicating a large gap between the two fields, which has not been previously detected by the prior benchmarks.
- Convolutional low-resolution fine-grained classification82
A novel resolution-aware deep model is proposed which combines convolutional image super-resolution and Convolutional fine-grained classification into a single model in an end-to-end manner and consistently performs better than conventional convolutionAL networks on classifying fine- grained object classes in low-resolution images.
- How to Make an RGBD Tracker?65
A generic framework for converting an arbitrary short-term RGB tracker into an RGBD tracker that is particularly powerful in occlusion scenarios where it provides 13.5% average improvement and 26% for the best tracker (CSR-DCF).
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- Urban 3D segmentation and modelling from street view images and LiDAR point clouds59
A novel methodology that takes GPS registered LiDAR point clouds and street view images as inputs and creates semantic labels for the 3D points clouds using a hybrid of rule-based parsing and learning-based labelling that combine point cloud and photometric features is proposed.
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- Anthropometric clothing measurements from 3D body scans54
A full processing pipeline to acquire anthropometric measurements from 3D measurements, based on non-rigid iterative closest point algorithm that minimizes overall energy of point distance and local stiffness energy terms is proposed.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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