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Found 9 papers, 1 papers with code
Synthetic Dialogue Dataset Generation using LLM Agents
We conduct human and automatic evaluations, including an evaluation approach that uses GPT-4 to mimic the human evaluation metrics.
MVC: A Multi-Task Vision Transformer Network for COVID-19 Diagnosis from Chest X-ray Images
Medical image analysis using computer-based algorithms has attracted considerable attention from the research community and achieved tremendous progress in the last decade.
Optimising complexity of CNN models for resource constrained devices: QRS detection case study
We hypothesize that a shallow CNN model can offer satisfactory level of performance in combination by leveraging other essential solution-components, such as post-processing that is suitable for resource constrained environment.
Double Attention-based Lightweight Network for Plant Pest Recognition
Moreover, the comparison results reveal that the proposed approach outperforms existing approaches on both small and large datasets consistently.
Learning post-processing for QRS detection using Recurrent Neural Network
To the best of our knowledge, the use of GRU to learn QRS-detection post-processing from CNN model generated prediction streams is the first of its kind.
Knowledge engineering mixed-integer linear programming: constraint typology
In this paper, we investigate the constraint typology of mixed-integer linear programming MILP formulations.
A Knowledge Representation Approach to Automated Mathematical Modelling
In the search for a suitable machine-readable knowledge representation structure for MILPs, we propose an optimization modelling tree built based upon an MILP model ontology that can be used as a guide for automated systems to elicit an MILP model from end-users on their combinatorial business optimization problems.
Choosing a sampling frequency for ECG QRS detection using convolutional networks
Automated QRS detection methods depend on the ECG data which is sampled at a certain frequency, irrespective of filter-based traditional methods or convolutional network (CNN) based deep learning methods.
Impact of ECG Dataset Diversity on Generalization of CNN Model for Detecting QRS Complex
In real life, a promising QRS detector may be expected to achieve acceptable accuracy over diverse ECG recordings and, thus, investigation of the model's generalization capability is crucial.
Ranked #1 on
QRS Complex Detection
on MIT-BIH AR
