1 citations · 3 across the 4 of their papers we have counts for
4 papers
Scaling Federated Learning Solutions with Kubernetes for Synthesizing Histopathology Images
Andrei-Alexandru Preda, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel
In the field of deep learning, large architectures often obtain the best performance for many tasks, but also require massive datasets. In the histological domain, tissue images ar…
Enhancing Romanian Offensive Language Detection through Knowledge Distillation, Multi-Task Learning, and Data Augmentation
Vlad-Cristian Matei, Iulian-Marius Tăiatu, Răzvan-Alexandru Smădu +1
This paper highlights the significance of natural language processing (NLP) within artificial intelligence, underscoring its pivotal role in comprehending and modeling human langua…
Explainability-Driven Leaf Disease Classification Using Adversarial Training and Knowledge Distillation
Sebastian-Vasile Echim, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel +1
This work focuses on plant leaf disease classification and explores three crucial aspects: adversarial training, model explainability, and model compression. The models' robustness…
Evaluating Data Augmentation Techniques for Coffee Leaf Disease Classification
Adrian Gheorghiu, Iulian-Marius Tăiatu, Dumitru-Clementin Cercel +2
The detection and classification of diseases in Robusta coffee leaves are essential to ensure that plants are healthy and the crop yield is kept high. However, this job requires ex…