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Found 8 papers, 1 papers with code
TRABSA: Interpretable Sentiment Analysis of Tweets using Attention-based BiLSTM and Twitter-RoBERTa
Sentiment analysis is crucial for understanding public opinion and consumer behavior.
From Image to Language: A Critical Analysis of Visual Question Answering (VQA) Approaches, Challenges, and Opportunities
The multimodal task of Visual Question Answering (VQA) encompassing elements of Computer Vision (CV) and Natural Language Processing (NLP), aims to generate answers to questions on any visual input.
A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges
In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas.
BaitBuster-Bangla: A Comprehensive Dataset for Clickbait Detection in Bangla with Multi-Feature and Multi-Modal Analysis
This study presents a large multi-modal Bangla YouTube clickbait dataset consisting of 253, 070 data points collected through an automated process using the YouTube API and Python web automation frameworks.
Addressing Uncertainty in Imbalanced Histopathology Image Classification of HER2 Breast Cancer: An interpretable Ensemble Approach with Threshold Filtered Single Instance Evaluation (SIE)
An ensemble approach integrated with threshold filtered single instance evaluation (SIE) technique has been proposed in this study to diagnose BC from the multi-categorical expression of HER2 subtypes.
QAmplifyNet: Pushing the Boundaries of Supply Chain Backorder Prediction Using Interpretable Hybrid Quantum-Classical Neural Network
Our proposed model, QAmplifyNet, employs quantum-inspired techniques within a quantum-classical neural network to predict backorders effectively on short and imbalanced datasets.
Big Data - Supply Chain Management Framework for Forecasting: Data Preprocessing and Machine Learning Techniques
This article intends to systematically identify and comparatively analyze state-of-the-art supply chain (SC) forecasting strategies and technologies.
convoHER2: A Deep Neural Network for Multi-Stage Classification of HER2 Breast Cancer
The outcomes of this study determined that the HER2 cancer detecting rates of the convoHER2 model are much enough to provide better diagnosis to the patient for recovering their HER2 breast cancer in future.
