Vehicular networks rely on periodic broadcast of each vehicle's state information to track its surrounding vehicles and therefore, to predict potential collisions. However, in a scenario of high vehicle density, a...
详细信息
This study comprehensively examines the ability to forecast the stability of smart grids using sophisticated deep learning and machine learning models. We investigate different approaches, such as Bidirectional Gated ...
详细信息
We devise a neural network-based temporal-textual framework that generates subgraphs with highly correlated authors from short-text contents. Our approach computes the relevance score (edge weight) between authors by ...
详细信息
Recognizing human activity using artificial intelligence and deep learning methods has become increasingly important in various fields, including medicine, sports, security, and wearable technology. With the rise of d...
详细信息
Understanding biodiversity, monitoring endangered species, and estimating the possible effect of climate change on particular regions all rely on animal species identification. Closed-circuit television (CCTV) cameras...
详细信息
This paper explores the transformative potential of Explainable Artificial Intelligence (XAI) in the context of coffee quality assessment, an area traditionally governed by subjective evaluation. By applying machine l...
详细信息
ISBN:
(纸本)9798350381771;9798350381764
This paper explores the transformative potential of Explainable Artificial Intelligence (XAI) in the context of coffee quality assessment, an area traditionally governed by subjective evaluation. By applying machine learning models, specifically a Random Forest Classifier enhanced by SHAP (SHapley Additive exPlanations) values, we identified crucial determinants of coffee quality, such as Category Two defects and high-altitude growth conditions. Our study demonstrates that machine learning can not only match but potentially exceed the accuracy of human experts in predicting coffee quality. More importantly, XAI has provided these models with a layer of transparency, making their complex predictions accessible and actionable for stakeholders in the coffee industry. This integration of AI into coffee quality assessment promises to standardize and optimize the evaluation process, offering a reliable guide for improving practices across the production chain. The findings underscore the broader impact of AI in agriculture, suggesting that such technology could be a harbinger of increased efficiency, sustainability, and trust in food production systems worldwide.
To achieve breakthrough performance in the task of dense crowd counting for unmanned aerial vehicles (UAVs) in complex environments, this paper introduces a multi-scale feature fusion crowd counting network model call...
详细信息
The most popular method for analysing a text is sentiment analysis. It is quite helpful for social media monitoring since it enables us to get a broad sense of what the general population thinks about particular issue...
详细信息
Aiming at the problems that the method based on U-shaped network for medical image segmentation cannot capture the long-range dependencies and could lose some detail information, a multi-scale context-aware segmentati...
详细信息
QKD, ECC, PQC, SMPC, and biometric-based authentication are examined in this work as essential information-theoretic security approaches. Each solution improves information-theoretic security by improving communicatio...
详细信息
暂无评论