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Deep learning for ultrasound medical images: artificial life variant
Segmentation of tumors in the ultrasound (US) images of the breast is a critical problem in medical imaging. Due to the poor quality of the US images...
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ProxMetrics: modular proxemic similarity toolkit to generate domain-adaptable indicators from social media
In this paper, we introduce ProxMetrics , a novel toolkit designed to evaluate similarity among social media entities through proxemic dimensions....
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Improving incentive policies to salespeople cross-sells: a cost-sensitive uplift modeling approach
In this study, we present a novel cost-sensitive approach for uplift modeling in the context of cross-selling and workforce analytics. We leverage...
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Search and Harvesting across NFDI Consortia – Gaps and Challenges
Search and harvesting use cases on harmonised metadata play an important role in several activities on National Research Data Infrastructures (NFDI)....
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A synthetic data generation system based on the variational-autoencoder technique and the linked data paradigm
Currently, the generation of synthetic data has become very fashionable, either due to the need to create data in certain specific contexts or to...
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Hybrid physics-infused 1D-CNN based deep learning framework for diesel engine fault diagnostics
Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result,...
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Twit-CoFiD: a hybrid recommender system based on tweet sentiment analysis
Internet users are overwhelmed by the vast number of services and products to choose from. This data deluge has led to the need for recommender...
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DSPformer: discovering semantic parts with token growth and clustering for zero-shot learning
Transformers have achieved success in many computer vision tasks, but their potential in Zero-Shot Learning (ZSL) has yet to be fully explored. In...
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An aviation accidents prediction method based on MTCNN and Bayesian optimization
The safety of the civil aviation system has been of increasing concern with several accidents in recent years. It is urgent to put forward a precise...
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Deep reinforcement learning-based scheduling in distributed systems: a critical review
Many fields of research use parallelized and distributed computing environments, including astronomy, earth science, and bioinformatics. Due to an...
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Injecting the score of the first-stage retriever as text improves BERT-based re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the...
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Optimization-based convolutional neural model for the classification of white blood cells
White blood cells (WBCs) are one of the most significant parts of the human immune system, and they play a crucial role in diagnosing the...
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Latent side-information dynamic augmentation for incremental recommendation
The incremental recommendation involves updating existing models by extracting information from interaction data at current time-step, with the aim...
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Bearing fault diagnosis using multiple feature selection algorithms with SVM
This paper presents an efficient approach to diagnose defects in various components of bearings in rotating machines using vibration signature...
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An overview of semantic-based process mining techniques: trends and future directions
Process mining algorithms essentially reflect the execution behavior of events in an event log for conformance checking, model discovery, or...
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Cores in multiway networks
The notion of a core is generalized to multiway networks. To determine the multiway cores, we adapted already-known algorithms for determining the...
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A digital pen-based writing state recognition algorithm for student performance assessment
Technology-enhanced learning is an irresistible trend in intelligent education. However, most digital pen-based studies focus on handwriting...
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Adversarial attacks and defenses for large language models (LLMs): methods, frameworks & challenges
Large language models (LLMs) have exhibited remarkable efficacy and proficiency in a wide array of NLP endeavors. Nevertheless, concerns are growing...
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One-way ticket to the moon? An NLP-based insight on the phenomenon of small-scale neo-broker trading
We present an Natural Language Processing based analysis on the phenomenon of “Meme Stocks”, which has emerged as a result of the proliferation of...
