207 citations · 213 across the 5 of their papers we have counts for
6 papers · 1 filter
FUSSL: Fuzzy Uncertain Self Supervised Learning
Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
Self supervised learning (SSL) has become a very successful technique to harness the power of unlabeled data, with no annotation effort. A number of developed approaches are evolvi…
Deep Active Ensemble Sampling For Image Classification
Salman Mohamadi, Gianfranco Doretto, Donald A. Adjeroh
Conventional active learning (AL) frameworks aim to reduce the cost of data annotation by actively requesting the labeling for the most informative data points. However, introducin…
Fine-Grained Visual Classification of Plant Species In The Wild: Object Detection as A Reinforced Means of Attention
Matthew R. Keaton, Ram J. Zaveri, Meghana Kovur +3
Plant species identification in the wild is a difficult problem in part due to the high variability of the input data, but also because of complications induced by the long-tail ef…
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
Stanislav Pidhorskyi, Ranya Almohsen, Donald A Adjeroh +1
Novelty detection is the problem of identifying whether a new data point is considered to be an inlier or an outlier. We assume that training data is available to describe only the…
Few-Shot Adversarial Domain Adaptation
Saeid Motiian, Quinn Jones, Seyed Mehdi Iranmanesh +1
This work provides a framework for addressing the problem of supervised domain adaptation with deep models. The main idea is to exploit adversarial learning to learn an embedded su…
Unified Deep Supervised Domain Adaptation and Generalization
Saeid Motiian, Marco Piccirilli, Donald A. Adjeroh +1
This work provides a unified framework for addressing the problem of visual supervised domain adaptation and generalization with deep models. The main idea is to exploit the Siames…