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VIRTUALLY THROWING BENCHMARKS INTO THE OCEAN FOR DEEP SEA PHOTOGRAMMETRY AND IMAGE PROCESSING EVALUATION [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Vision in the deep sea is acquiring increasing interest from many fields as the deep seafloor represents the largest surface portion on Earth. Unlike common shallow underwater imaging, deep sea imaging requires artificial lighting to illuminate the scene
Y. Song, M. She, K. Köser
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Open Research Europe, 2022 To overcome the data scarcity problem of machine learning for nondestructive testing, data augmentation is a commonly used strategy. We propose a method to enable training of neural networks exclusively on simulated data.
Klaus Schlachter +2 more
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CVML-Pose: Convolutional VAE Based Multi-Level Network for Object 3D Pose Estimation
IEEE Access, 2023 Most vision-based 3D pose estimation approaches typically rely on knowledge of object’s 3D model, depth measurements, and often require time-consuming iterative refinement to improve accuracy.
Jianyu Zhao +2 more
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Electronics Letters, 2023 Deep learning models have been widely applied in video‐based depression detection. It is observed that the diversity of preprocessing, data augmentation, and optimization techniques makes it difficult to fairly compare model architectures. In this study,
Manuel Lage Cañellas +3 more
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Fast Light Field Angular Resolution Enhancement Using Convolutional Neural Network
IEEE Access, 2021 Current light field angular super-resolution algorithm based on deep learning has excessive computation cost and low operational efficiency, for sequentially up-sampling on each lenslet region of the light field image.
Xingzheng Wang +3 more
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Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights
Frontiers in Veterinary Science, 2022 Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying state of
Mark F. Hansen +5 more
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A Novel Time-Aware Food Recommender-System Based on Deep Learning and Graph Clustering
IEEE Access, 2022 Food recommender-systems are considered an effective tool to help users adjust their eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food recommender-system to overcome the shortcomings of previous systems, such as ...
Mehrdad Rostami +2 more
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Microaneurysm detection in fundus images using a two-step convolutional neural network
BioMedical Engineering OnLine, 2019 Background and objectives Diabetic retinopathy (DR) is the leading cause of blindness worldwide, and therefore its early detection is important in order to reduce disease-related eye injuries. DR is diagnosed by inspecting fundus images.
Noushin Eftekhari +4 more
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The IPRS Image Processing and Pattern Recognition System. [PDF]
, 1997 IPRS is a freely available software system which consists of about 250 library functions in C, and a set of application programs. It is designed to run under UNIX and comes with full source code, system manual pages, and a comprehensive user's and ...
Caelli, Terry +3 more
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Fast Convolutional Method for Automatic Sleep Stage Classification [PDF]
Healthcare Informatics Research, 2018 ObjectivesPolysomnography is essential to diagnose sleep disorders. It is used to identify a patient's sleep pattern during sleep. This pattern is obtained by a doctor or health practitioner by using a scoring process, which is time consuming.
Intan Nurma Yulita +2 more
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