11 citations · 14 across the 9 of their papers we have counts for
9 papers
Meta-Learning for Data-Efficient Plant Growth Estimation via Vision Transformers and Fuzzy Clustering
Sheikh Hasan Elahi, Rusith Chamara Hathurusinghe Dewage, Habib Ullah +3
Accurate plant growth estimation is essential for greenhouse monitoring, yet obtaining labeled data remains costly and time-consuming. To address this, we propose a few-shot regres…
Towards Continual Test-Time Adaptation of Vision-Language Models in Open-Vocabulary Semantic Segmentation
Chandler Timm C. Doloriel, Yunbei Zhang, Sarthak Kumar Maharana +5
Open-vocabulary semantic segmentation (OVSS) relies on vision-language alignment to recognize arbitrary text-defined categories, yet this alignment is fragile under continual test-…
Continual Test-Time Adaptation via Entropy Sensitivity-Guidance in Strict Online Setting
Chandler Timm C. Doloriel, Yunbei Zhang, Muhammad Salman Siddiqui +4
Test-time adaptation (TTA) promises robustness under distribution shift by updating a pretrained model on unlabeled test data, but strict online TTA with batch size one and no acce…
CAST: Closed-form Analytic Semantic Transfer for Zero-Shot Classifier Extension
William Heyden, Habib Ullah, Muhammad Salman Siddiqui +1
Large pre-trained models have become foundational components of modern machine learning systems. Yet adapting these models to novel categories typically requires examples from the…
PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations
Pavel Iakovets, Liyanapathiranage Sudeepika Wajirakumari Samarathunga, Martin Thomas Horsch +1
Counterfactual explanations explain machine learning predictions by identifying minimal input changes that would alter a model's decision. Although many existing methods successful…
NASP-T: A Fuzzy Neuro-Symbolic Transformer for Logic-Constrained Aviation Safety Report Classification
Fadi Al Machot, Fidaa Al Machot
Deep transformer models excel at multi-label text classification but often violate domain logic that experts consider essential, an issue of particular concern in safety-critical a…
Bridging Logic and Learning: A Neural-Symbolic Approach for Enhanced Reasoning in Neural Models (ASPER)
Fadi Al Machot
Neural-symbolic learning, an intersection of neural networks and symbolic reasoning, aims to blend neural networks' learning capabilities with symbolic AI's interpretability and re…
SEER-ZSL: Semantic Encoder-Enhanced Representations for Generalized Zero-Shot Learning
William Heyden, Habib Ullah, M. Salman Siddiqui +1
Zero-Shot Learning (ZSL) presents the challenge of identifying categories not seen during training. This task is crucial in domains where it is costly, prohibited, or simply not fe…
A Comprehensive Review of Automated Data Annotation Techniques in Human Activity Recognition
Florenc Demrozi, Cristian Turetta, Fadi Al Machot +2
Human Activity Recognition (HAR) has become one of the leading research topics of the last decade. As sensing technologies have matured and their economic costs have declined, a ho…