Titlebook: Computer Vision Systems; 14th International C Henrik I. Christensen,Peter Corke,Markus Vincze Conference proceedings 2023 The Editor(s) (if

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Residual Cascade CNN for?Detection of?Spatially Relevant Objects in?Agriculture: The Grape-Stem Parace costs. However, working on the agriculture domain introduces important challenges, such as adverse conditions, small structures and lack of large datasets, hindering its wide adoption on multiple cases. This work presents an approach to improve the performance of detecting challenging small objec

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Tracking and?Identification of?Ice Hockey Playerse game..Experiments conducted with data collected from actual ice hockey games demonstrate the viability of our proposed framework for tracking and identifying players in real-world settings. Our framework achieves an average precision (AP) of 67.3 and a Multiple Object Tracking Accuracy (MOTA) of 8

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Non-contact Heart Rate Monitoring: A Comparative Study of Computer Vision and Radar Approachesfor both CV and mm-wave radar systems and characterises their HR estimation performance, using electrocardiography (ECG) to provide ground truth measurements. The effects of distance to sensors and of illumination variations on HR estimation are also studied, showing the relative errors for both mod

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CFAB: An Online Data Augmentation to?Alleviate the?Spuriousness of?Classification on?Medical Ultrasoramework for collaborative augmenting samples using CFAB and training CNNs. Comprehensive experiments indicate that the proposed method weakens the spuriousness, improves the generalizability of the model, and achieves state-of-the-art results in medical ultrasound dataset classification.

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Of Mice and?Pose: 2D Mouse Pose Estimation from?Unlabelled Data and?Synthetic Priorbtained ground truth. We also compare predictions with those from a supervised state-of-the-art method for animal pose estimation. The latter evaluation indicates promising results despite the lack of paired training data. Finally, qualitative results using a dataset of horse images show the potenti

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Key Point-Based Orientation Estimation of?Strawberries for?Robotic Fruit Pickingworld scenarios. Our method achieves state-of-the-art performance with an average error as low as ., improving predictions by .30% compared to previous work presented in?[.]. Furthermore, our method is suited for real-time robotic applications with fast inference times of .30 ms.