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A hyperparameter study for quantum kernel methods
Quantum kernel methods are a promising method in quantum machine learning thanks to the guarantees connected to them. Their accessibility for...
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Social Assistive Robotics: An Ethical and Political Inquiry Through the Lens of Freedom
The development of social assistive robots for supporting healthcare provision faces a lack of an ethical approach that adequately addresses the...
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Improved genetic algorithm based on reinforcement learning for electric vehicle front-end structure optimization design
The structural optimization of electric vehicles involves numerous design variables and constraints, making it a complex engineering optimization...
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MGA-Net: multiscale global feature aggregation network for arteriovenous classification
Subtle retinal vascular changes and abnormalities can serve as crucial biomarkers for numerous systemic diseases. The classification of retinal...
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The ethics of personalised digital duplicates: a minimally viable permissibility principle
With recent technological advances, it is possible to create personalised digital duplicates. These are partial, at least semi-autonomous,...
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Extra-abdominal trocar and instrument detection for enhanced surgical workflow understanding
PurposeVideo-based intra-abdominal instrument tracking for laparoscopic surgeries is a common research area. However, the tracking can only be done...
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Hybrid genetic optimization for quantum feature map design
Kernel methods are an import class of techniques in machine learning. To be effective, good feature maps are crucial for map** non-linearly...
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3D-Scene-Former: 3D scene generation from a single RGB image using Transformers
3D scene generation requires complex hardware setups, such as multiple cameras and depth sensors. To address this challenge, there is a need for...
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Dual-view graph convolutional network for multi-label text classification
Multi-label text classification refers to assigning multiple relevant category labels to each text, which has been widely applied in the real world....
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Reading Between the Lines: Machine Learning Ensemble and Deep Learning for Implied Threat Detection in Textual Data
With the increase in the generation and spread of textual content on social media, natural language processing (NLP) has become an important area of...
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CommentClass: A Robust Ensemble Machine Learning Model for Comment Classification
Enormous amounts of data are generated in the form of feedback or comments from online platforms such as social media, e-commerce, education, and...
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Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena
To learn about real world phenomena, scientists have traditionally used models with clearly interpretable elements. However, modern machine learning...
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ASR-Fed: agnostic straggler-resilient semi-asynchronous federated learning technique for secured drone network
Federated Learning (FL) has emerged as a transformative artificial intelligence paradigm, facilitating knowledge sharing among distributed edge...
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A Multi-strategy Slime Mould Algorithm for Solving Global Optimization and Engineering Optimization Problems
Aiming at the problems of slow convergence, low accuracy, and easy to fall into local optimum of the slime mould algorithm (SMA), we propose an...
