All Outputs (15)

ResNet18 performance: Impact of network depth and image resolution on image classification (2024)
Presentation / Conference Contribution

This study explores aspects of using ResNet18 for the classification of biomedical images, using the 2D medical images from the MedMNIST library that is widely used for benchmarking. The number of layers within the ResNet18 was studied. The typically... Read More about ResNet18 performance: Impact of network depth and image resolution on image classification.

Examining neural networks through architectural variation analysis for image classification (2024)
Presentation / Conference Contribution

This paper presents a method for examining neural networks in image classification through architectural variation analysis. Small-scale experiments generate initial insights, and the configurations are further tested on entire datasets. The newly pr... Read More about Examining neural networks through architectural variation analysis for image classification.

On Cooperative Coevolution and Global Crossover (2024)
Journal Article

Cooperative coevolutionary algorithms (CCEAs) divide a given problem in to a number of subproblems and use an evolutionary algorithm to solve each subproblem. This letter is concerned with the scenario under which a single fitness measure exists. By... Read More about On Cooperative Coevolution and Global Crossover.

A systematic review of machine-learning solutions in anaerobic digestion (2023)
Journal Article

The use of machine learning (ML) in anaerobic digestion (AD) is growing in popularity and improves the interpretation of complex system parameters for better operation and optimisation. This systematic literature review aims to explore how ML is curr... Read More about A systematic review of machine-learning solutions in anaerobic digestion.

Reproducing "Show, attend and tell: Neural image caption generation with visual attention" (2023)
Presentation / Conference Contribution

This paper replicates the experiment presented in the work of Xu et al. [1], and
examines errors in the generated captions. The analysis of the identified errors aims to provide
deeper insight into the underlying causes. This study also encompass... Read More about Reproducing "Show, attend and tell: Neural image caption generation with visual attention".

Towards idea mining: Problem-solution phrase extraction from text (2022)
Presentation / Conference Contribution

This paper investigates the feasibility of problem-solution phrases extraction from scientific publications using neural network approaches. Bidirectional Long Short-Term Memory with Conditional Random Fields (Bi-LSTM-CRFs) and Bidirectional Encoder... Read More about Towards idea mining: Problem-solution phrase extraction from text.

Towards idea mining: Problem-solution phrases extraction from text (2022)
Presentation / Conference Contribution

This paper investigates the feasibility of problem-solution
phrases extraction from scientific publications using neural network approaches. Bidirectional Long Short-Term Memory with Conditional Random Fields (Bi-LSTM-CRFs) and Bidirectional Encoder... Read More about Towards idea mining: Problem-solution phrases extraction from text.

A generalised dropout mechanism for distributed systems (2022)
Journal Article

This letter uses a modified form of the NK model introduced to explore aspects of distributed control. In particular, a previous result suggesting the use of dynamically formed subgroups within the overall system can be more effective than global con... Read More about A generalised dropout mechanism for distributed systems.

Citation sentiment changes analysis (2020)
Preprint / Working Paper

Metrics for measuring the citation sentiment changes were introduced. Citation sentiment changes can be observed from global citation sentiment sequences (GCSSs). With respect to a cited paper, the citation sentiment sequences were analysed across a... Read More about Citation sentiment changes analysis.

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: Sequential fine-tuning (2018)
Journal Article

Bronchoscopy inspection, as a follow-up procedure next to the radiological imaging, plays a key role in the diagnosis and treatment design for lung disease patients. When performing bronchoscopy, doctors have to make a decision immediately whether to... Read More about Optimize transfer learning for lung diseases in bronchoscopy using a new concept: Sequential fine-tuning.

Sentiment analysis of citations using word2vec (2017)
Preprint / Working Paper

Citation sentiment analysis is an important task in scientific paper analysis. Existing machine learning techniques for citation sentiment analysis are focusing on labor-intensive feature engineering, which requires large annotated corpus. As an auto... Read More about Sentiment analysis of citations using word2vec.

Automatic argumentative-zoning using word2vec (2017)
Preprint / Working Paper

In comparison with document summarization on the articles from social media and newswire, argumentative zoning (AZ) is an important task in scientific paper analysis. Traditional methodology to carry on this task relies on feature engineering from di... Read More about Automatic argumentative-zoning using word2vec.

Towards computation of novel ideas from corpora of scientific text (2015)
Presentation / Conference Contribution

© Springer International Publishing Switzerland 2015. In this work we present a method for the computation of novel ‘ideas’ from corpora of scientific text. The system functions by first detecting concept noun-phrases within the titles and abstracts... Read More about Towards computation of novel ideas from corpora of scientific text.

Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound (2014)
Journal Article

We investigated the benefits of incorporating texture features into an existing computer-aided diagnosis (CAD) system for classifying benign and malignant lesions in automated three-dimensional breast ultrasound images. The existing system takes into... Read More about Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound.

A method for finding implicating rules based on the genetic algorithm (2007)
Presentation / Conference Contribution

In information system, some rules have implicating relations (called implicating rules), but some rules have not. An approach of finding implicating rules based on the genetic algorithm is proposed. Some properties of independence and correlation of... Read More about A method for finding implicating rules based on the genetic algorithm.