Results 21 to 30 of about 901,000 (263)
Few-Shot Image Classification via Mutual Distillation
Applied Sciences, 2023 Due to their compelling performance and appealing simplicity, metric-based meta-learning approaches are gaining increasing attention for addressing the challenges of few-shot image classification.
Tianshu Zhang +5 more
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POLSAR Image Classification via Clustering-WAE Classification Model
IEEE Access, 2018 Considering the clustering algorithms could explore the label information automatically, this paper proposes a new method in terms of polarimetric synthetic aperture radar (POLSAR) image classification, which named a clustering-wishart-auto-encoder (WAE)
Wen Xie, Ziwei Xie, Feng Zhao, Bo Ren
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Glomerulus Classification via an Improved GoogLeNet
IEEE Access, 2020 Glomerulosclerosis is a pathomorphological feature of glomerular lesions. Early detection, accurate judgement and effective prevention of the glomeruli is crucial not only for people with kidney disease, but also for the general population. We proposed a
Xujing Yao +4 more
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Mapping strengths into virtues: The relation of the 24 VIA-strengths to six ubiquitous virtues
Frontiers in Psychology, 2015 The Values-in-Action (VIA)-classification distinguishes six core virtues and 24 strengths. As the assignment of the strengths to the virtues was done on theoretical grounds it still needs empirical verification.
Willibald eRuch, René T Proyer
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Validating deep learning seabed classification via acoustic similarity [PDF]
JASA Express Letters, 2021 While seabed characterization methods have often focused on estimating individual sediment parameters, deep learning suggests a class-based approach focusing on the overall acoustic effect.
David J. Forman +3 more
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Texture classification via conditional histograms [PDF]
Pattern Recognition Letters, 2005 This paper presents a non-parametric discrimination strategy based on texture features characterised by one-dimensional conditional histograms. Our characterisation extends previous co-occurrence matrix encoding schemes by considering a mixture of colour and contextual information obtained from binary images.
Eugenia Montiel +2 more
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, 2006 Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised manner, and to use this object distribution to perform scene classification.
Bosch, A, Zisserman, A, Muñoz, X
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Character Strengths Profiles in Medical Professionals and Their Impact on Well-Being
Frontiers in Psychology, 2020 Character strengths profiles in the specific setting of medical professionals are widely unchartered territory. This paper focused on an overview of character strengths profiles of medical professionals (medical students and physicians) based on ...
Alexandra Huber +5 more
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Multi-View Classification via Adaptive Discriminant Analysis
IEEE Access, 2019 In many real applications, an object is usually represented with multiple views, providing compatible and complementary information to each other. Therefore, it is highly desirable to recognize the object from distinct and even heterogeneous views.
Deyan Xie +5 more
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Action Classification via Concepts and Attributes [PDF]
2018 24th International Conference on Pattern Recognition (ICPR), 2018 Classes in natural images tend to follow long tail distributions. This is problematic when there are insufficient training examples for rare classes. This effect is emphasized in compound classes, involving the conjunction of several concepts, such as those appearing in action-recognition datasets.
Amir Rosenfeld, Shimon Ullman
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