28 citations · 177 across the 28 of their papers we have counts for
7 papers · 1 filter
Semantic-Based Few-Shot Learning by Interactive Psychometric Testing
Lu Yin, Vlado Menkovski, Yulong Pei +1
Few-shot classification tasks aim to classify images in query sets based on only a few labeled examples in support sets. Most studies usually assume that each image in a task has a…
Hierarchical Semantic Segmentation using Psychometric Learning
Lu Yin, Vlado Menkovski, Shiwei Liu +1
Assigning meaning to parts of image data is the goal of semantic image segmentation. Machine learning methods, specifically supervised learning is commonly used in a variety of tas…
Micro-expression detection in long videos using optical flow and recurrent neural networks
Michiel Verburg, Vlado Menkovski
Facial micro-expressions are subtle and involuntary expressions that can reveal concealed emotions. Micro-expressions are an invaluable source of information in application domains…
StampNet: unsupervised multi-class object discovery
Joost Visser, Alessandro Corbetta, Vlado Menkovski +1
Unsupervised object discovery in images involves uncovering recurring patterns that define objects and discriminates them against the background. This is more challenging than imag…
Weakly supervised training of deep convolutional neural networks for overhead pedestrian localization in depth fields
Alessandro Corbetta, Vlado Menkovski, Federico Toschi
Overhead depth map measurements capture sufficient amount of information to enable human experts to track pedestrians accurately. However, fully automating this process using image…
Understanding Anatomy Classification Through Attentive Response Maps
Devinder Kumar, Vlado Menkovski, Graham W. Taylor +1
One of the main challenges for broad adoption of deep learning based models such as convolutional neural networks (CNN), is the lack of understanding of their decisions. In many ap…
Can Pretrained Neural Networks Detect Anatomy?
Vlado Menkovski, Zharko Aleksovski, Axel Saalbach +1
Convolutional neural networks demonstrated outstanding empirical results in computer vision and speech recognition tasks where labeled training data is abundant. In medical imaging…