Defect detection using weakly supervised learning

no code implementations • 27 Mar 2023 • Vasileios Sevetlidis, George Pavlidis, Vasiliki Balaska, Athanasios Psomoulis, Spyridon Mouroutsos, Antonios Gasteratos

In many real-world scenarios, obtaining large amounts of labeled data can be a daunting task.

Defect Detection Weakly-supervised Learning

Dens-PU: PU Learning with Density-Based Positive Labeled Augmentation

no code implementations • 21 Mar 2023 • Vasileios Sevetlidis, George Pavlidis, Spyridon Mouroutsos, Antonios Gasteratos

Once a set of negative samples is obtained, the PU learning problem reduces to binary classification.

Anomaly Detection Binary Classification

Do Neural Network Weights account for Classes Centers?

1 code implementation • 14 Apr 2021 • Ioannis Kansizoglou, Loukas Bampis, Antonios Gasteratos

The exploitation of Deep Neural Networks (DNNs) as descriptors in feature learning challenges enjoys apparent popularity over the past few years.

Fast and Incremental Loop Closure Detection with Deep Features and Proximity Graphs

2 code implementations • 29 Sep 2020 • Shan An, Haogang Zhu, Dong Wei, Konstantinos A. Tsintotas, Antonios Gasteratos

In recent years, the robotics community has extensively examined methods concerning the place recognition task within the scope of simultaneous localization and mapping applications. This article proposes an appearance-based loop closure detection pipeline named ``FILD++" (Fast and Incremental Loop closure Detection). First, the system is fed by consecutive images and, via passing them twice through a single convolutional neural network, global and local deep features are extracted. Subsequently, a hierarchical navigable small-world graph incrementally constructs a visual database representing the robot's traversed path based on the computed global features. Finally, a query image, grabbed each time step, is set to retrieve similar locations on the traversed route. An image-to-image pairing follows, which exploits local features to evaluate the spatial information.

Loop Closure Detection Simultaneous Localization and Mapping

HASeparator: Hyperplane-Assisted Softmax

no code implementations • 8 Aug 2020 • Ioannis Kansizoglou, Nicholas Santavas, Loukas Bampis, Antonios Gasteratos

Efficient feature learning with Convolutional Neural Networks (CNNs) constitutes an increasingly imperative property since several challenging tasks of computer vision tend to require cascade schemes and modalities fusion.

Image Classification

Deep Feature Space: A Geometrical Perspective

1 code implementation • 30 Jun 2020 • Ioannis Kansizoglou, Loukas Bampis, Antonios Gasteratos

One of the most prominent attributes of Neural Networks (NNs) constitutes their capability of learning to extract robust and descriptive features from high dimensional data, like images.

Descriptive Reinforcement Learning (RL)

Attention! A Lightweight 2D Hand Pose Estimation Approach

1 code implementation • 22 Jan 2020 • Nicholas Santavas, Ioannis Kansizoglou, Loukas Bampis, Evangelos Karakasis, Antonios Gasteratos

Vision based human pose estimation is an non-invasive technology for Human-Computer Interaction (HCI).

Hand Pose Estimation