Ali Braytee
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View article: Detecting and Understanding Hateful Contents in Memes Through Captioning and Visual Question-Answering
Detecting and Understanding Hateful Contents in Memes Through Captioning and Visual Question-Answering Open
Memes are widely used for humor and cultural commentary, but they are increasingly exploited to spread hateful content. Due to their multimodal nature, hateful memes often evade traditional text-only or image-only detection systems, partic…
View article: Simplified Swarm Learning Framework for Robust and Scalable Diagnostic Services in Cancer Histopathology
Simplified Swarm Learning Framework for Robust and Scalable Diagnostic Services in Cancer Histopathology Open
The complexities of healthcare data, including privacy concerns, imbalanced datasets, and interoperability issues, necessitate innovative machine learning solutions. Swarm Learning (SL), a decentralized alternative to Federated Learning, o…
View article: DualPrompt-MedCap: A Dual-Prompt Enhanced Approach for Medical Image Captioning
DualPrompt-MedCap: A Dual-Prompt Enhanced Approach for Medical Image Captioning Open
Medical image captioning via vision-language models has shown promising potential for clinical diagnosis assistance. However, generating contextually relevant descriptions with accurate modality recognition remains challenging. We present …
View article: AeroLite: Tag-Guided Lightweight Generation of Aerial Image Captions
AeroLite: Tag-Guided Lightweight Generation of Aerial Image Captions Open
Accurate and automated captioning of aerial imagery is crucial for applications like environmental monitoring, urban planning, and disaster management. However, this task remains challenging due to complex spatial semantics and domain vari…
View article: Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging
Vision Transformers with Autoencoders and Explainable AI for Cancer Patient Risk Stratification Using Whole Slide Imaging Open
Cancer remains one of the leading causes of mortality worldwide, necessitating accurate diagnosis and prognosis. Whole Slide Imaging (WSI) has become an integral part of clinical workflows with advancements in digital pathology. While vari…
View article: FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation
FedSAF: A Federated Learning Framework for Enhanced Gastric Cancer Detection and Privacy Preservation Open
Gastric cancer is one of the most commonly diagnosed cancers and has a high mortality rate. Due to limited medical resources, developing machine learning models for gastric cancer recognition provides an efficient solution for medical inst…
View article: Enhancing Sentiment Analysis through Multimodal Fusion: A BERT-DINOv2 Approach
Enhancing Sentiment Analysis through Multimodal Fusion: A BERT-DINOv2 Approach Open
Multimodal sentiment analysis enhances conventional sentiment analysis, which traditionally relies solely on text, by incorporating information from different modalities such as images, text, and audio. This paper proposes a novel multimod…
View article: Visual and Text Prompt Segmentation: A Novel Multi-Model Framework for Remote Sensing
Visual and Text Prompt Segmentation: A Novel Multi-Model Framework for Remote Sensing Open
Pixel-level segmentation is essential in remote sensing, where foundational vision models like CLIP and Segment Anything Model(SAM) have demonstrated significant capabilities in zero-shot segmentation tasks. Despite their advances, challen…
View article: Fine-Tuning LLMs for Reliable Medical Question-Answering Services
Fine-Tuning LLMs for Reliable Medical Question-Answering Services Open
We present an advanced approach to medical question-answering (QA) services, using fine-tuned Large Language Models (LLMs) to improve the accuracy and reliability of healthcare information. Our study focuses on optimizing models like LLaMA…
View article: Explainable AI Methods for Multi-Omics Analysis: A Survey
Explainable AI Methods for Multi-Omics Analysis: A Survey Open
Advancements in high-throughput technologies have led to a shift from traditional hypothesis-driven methodologies to data-driven approaches. Multi-omics refers to the integrative analysis of data derived from multiple 'omes', such as genom…
View article: Optimized Biomedical Question-Answering Services with LLM and Multi-BERT Integration
Optimized Biomedical Question-Answering Services with LLM and Multi-BERT Integration Open
We present a refined approach to biomedical question-answering (QA) services by integrating large language models (LLMs) with Multi-BERT configurations. By enhancing the ability to process and prioritize vast amounts of complex biomedical …
View article: RETRACTED: Sankar et al. Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology. BioMedInformatics 2024, 4, 1059–1070
RETRACTED: Sankar et al. Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology. BioMedInformatics 2024, 4, 1059–1070 Open
The journal retracts the article, “Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology” [...]
View article: Machine learning to predict the intrinsic membrane parameters in pressure retarded osmosis for an economic salinity gradient power plant
Machine learning to predict the intrinsic membrane parameters in pressure retarded osmosis for an economic salinity gradient power plant Open
Pressure retarded osmosis (PRO) is highly investigated in the literature as one of the blue energy techniques. The PRO membrane plays a key role in harvesting the osmotic energy from a salinity gradient resource and process optimization. T…
View article: Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis
Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis Open
Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-…
View article: A Novel Dual-Pipeline based Attention Mechanism for Multimodal Social Sentiment Analysis
A Novel Dual-Pipeline based Attention Mechanism for Multimodal Social Sentiment Analysis Open
Traditionally, sentiment analysis methods rely solely on text or image data. However, most user-generated social media content includes both textual and image content. In this study, we propose a novel Dual-Pipeline based Attentional metho…
View article: Ensemble Pretrained Models for Multimodal Sentiment Analysis using Textual and Video Data Fusion
Ensemble Pretrained Models for Multimodal Sentiment Analysis using Textual and Video Data Fusion Open
We introduce an ensemble model approach for multimodal sentiment analysis, focusing on the fusion of textual and video data to enhance the accuracy and depth of emotion interpretation. By integrating three foundational models-IFFSA, BFSA, …
View article: Integration of Self-Supervised BYOL in Semi-Supervised Medical Image Recognition
Integration of Self-Supervised BYOL in Semi-Supervised Medical Image Recognition Open
Image recognition techniques heavily rely on abundant labeled data, particularly in medical contexts. Addressing the challenges associated with obtaining labeled data has led to the prominence of self-supervised learning and semi-supervise…
View article: Early Parkinson’s Disease Diagnosis through Hand-Drawn Spiral and Wave Analysis Using Deep Learning Techniques
Early Parkinson’s Disease Diagnosis through Hand-Drawn Spiral and Wave Analysis Using Deep Learning Techniques Open
Parkinson’s disease (PD) is a chronic brain disorder affecting millions worldwide. It occurs when brain cells that produce dopamine, a chemical controlling movement, die or become damaged. This leads to PD, which causes problems with movem…
View article: RETRACTED: Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology
RETRACTED: Utilizing Generative Adversarial Networks for Acne Dataset Generation in Dermatology Open
Background: In recent years, computer-aided diagnosis for skin conditions has made significant strides, primarily driven by artificial intelligence (AI) solutions. However, despite this progress, the efficiency of AI-enabled systems remain…
View article: Robust multi-label feature learning-based dual space
Robust multi-label feature learning-based dual space Open
Multi-label learning handles instances associated with multiple class labels. The original label space is a logical matrix with entries from the Boolean domain $$\in \left\{ 0,1 \right\} $$ . Logical labels cannot show the relative …
View article: Identification of Cancer Risk Groups through Multi-Omics Integration using Autoencoder and Tensor Analysis
Identification of Cancer Risk Groups through Multi-Omics Integration using Autoencoder and Tensor Analysis Open
Identifying cancer risk groups by integrative multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinici…
View article: SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation
SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation Open
This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations. We accomplish this goal by a simple yet effective self-superv…
View article: Detecting Human Falls in Poor Lighting: Object Detection and Tracking Approach for Indoor Safety
Detecting Human Falls in Poor Lighting: Object Detection and Tracking Approach for Indoor Safety Open
Falls are one the leading causes of accidental death for all people, but the elderly are at particularly high risk. Falls are severe issue in the care of those elderly people who live alone and have limited access to health aides and skill…
View article: SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation
SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation Open
This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations. We accomplish this goal by a simple yet effective self-superv…
View article: A Benchmark of Pre-processing Effect on Single Cell RNA Sequencing Integration Methods
A Benchmark of Pre-processing Effect on Single Cell RNA Sequencing Integration Methods Open
Single-cell data analysis can transform the practice of personalised medicine by facilitating characterisation of disease-associated molecular changes across every single cell. Advanced single-cell multimodal assays can now simultaneously …
View article: Multi-objective variational autoencoder: an application for smart infrastructure maintenance
Multi-objective variational autoencoder: an application for smart infrastructure maintenance Open
Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order data sets where standard two-way analysis techniques often fail to discover the hidden correlations between variables in multi-way dat…