A comprehensive systematic review of machine learning in the retail industry: classifications, limitations, opportunities, and challenges
Abstract Machine learning has profoundly transformed various industries, notably
revolutionizing the retail sector through diverse applications that significantly enhance …
revolutionizing the retail sector through diverse applications that significantly enhance …
Sustainable Coffee Leaf Diagnosis: A Deep Knowledgeable Meta-Learning Approach
AA Salamai, WT Al-Nami - Sustainability, 2023 - mdpi.com
Multi-task visual recognition plays a pivotal role in addressing the composite challenges
encountered during the monitoring of crop health, pest infestations, and disease outbreaks …
encountered during the monitoring of crop health, pest infestations, and disease outbreaks …
A predictive model for the estimation of industrial PM2. 5 emissions for IoT-based devices
A Kychkin, O Vikenteva, L Mylnikov… - Computers & Industrial …, 2024 - Elsevier
The paper is devoted to solving the problem, associated with increasing the forecasting
accuracy of pollutant concentration level based on PM 2. 5 dust. The LANN model (LANN …
accuracy of pollutant concentration level based on PM 2. 5 dust. The LANN model (LANN …
Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques
Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating
the development of accurate and reliable predictive models to facilitate early detection and …
the development of accurate and reliable predictive models to facilitate early detection and …
Integrative Deep Learning Forecasting of Air Quality Index in India: A Fusion of Bidirectional LSTM and Sensor Data
BM Mudhanai Sanjeevirayar, G Mudhana… - Proceedings of the …, 2023 - dl.acm.org
AQI as a vital metric for evaluating pollution levels, which directly impacts the health and well-
being of the population. We have devised a hybrid deep learning (DL) framework that …
being of the population. We have devised a hybrid deep learning (DL) framework that …
[PDF][PDF] Adversarial transfer learning based hybrid recurrent network for air quality prediction
Y Hao, C Luo, T Li, J Zhang, H Chen - 2024 - assets-eu.researchsquare.com
Air quality modeling and forecasting has become a key problem in environmental protection.
The existing prediction models typically require large-scale and high-quality historical data …
The existing prediction models typically require large-scale and high-quality historical data …
[PDF][PDF] Sustainable Coffee Leaf Diagnosis: A Deep Knowledgeable Meta-Learning Approach. Sustainability 2023, 15, 16791
AA Salamai, WT Al-Nami - 2023 - academia.edu
Multi-task visual recognition plays a pivotal role in addressing the composite challenges
encountered during the monitoring of crop health, pest infestations, and disease outbreaks …
encountered during the monitoring of crop health, pest infestations, and disease outbreaks …
Air quality index prediction for clearer skies using improved long short-term memory
NB Bahadure, O Sahare, N Shukla… - Intelligent Decision … - content.iospress.com
Air pollution has become an international calamity, a problem for human health and the
environment. The ability to predict the air quality becomes a crucial task. The usual …
environment. The ability to predict the air quality becomes a crucial task. The usual …