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Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms
Today, the world's primary energy demand has been met by the burning of fossil-based fuels
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …
at a rate of 85%. This dominant use of fossil-based fuels has led to an accelerating increase …
A review of Urdu sentiment analysis with multilingual perspective: A case of Urdu and roman Urdu language
Research efforts in the field of sentiment analysis have exponentially increased in the last
few years due to its applicability in areas such as online product purchasing, marketing, and …
few years due to its applicability in areas such as online product purchasing, marketing, and …
A wearable multidimensional motion sensor for AI-enhanced VR sports
Regular exercise paves the way to a healthy life. However, conventional sports events are
susceptible to weather conditions. Current motion sensors for home-based sports are mainly …
susceptible to weather conditions. Current motion sensors for home-based sports are mainly …
Raman spectroscopy and FTIR spectroscopy fusion technology combined with deep learning: A novel cancer prediction method
H Leng, C Chen, C Chen, F Chen, Z Du, J Chen… - … Acta Part A: Molecular …, 2023 - Elsevier
According to the limited molecular information reflected by single spectroscopy, and the
complementarity of FTIR spectroscopy and Raman spectroscopy, we propose a novel …
complementarity of FTIR spectroscopy and Raman spectroscopy, we propose a novel …
A federated machine learning approach for order-level risk prediction in supply chain financing
Abstract Supply Chain Financing (SCF) is increasingly utilised as an effective method for
optimising cash flows in supply networks. With increased popularity several financial …
optimising cash flows in supply networks. With increased popularity several financial …
CNN-based person detection using infrared images for night-time intrusion warning systems
Night-time surveillance is important for safety and security purposes. For this reason, several
studies have attempted to automatically detect people intruding into restricted areas by …
studies have attempted to automatically detect people intruding into restricted areas by …
[PDF][PDF] Plant disease detection using CNN
E Harte - ResearchGate, 2020 - researchgate.net
Plant disease is an ongoing challenge for smallholder farmers, which threatens income and
food security. The recent revolution in smartphone penetration and computer vision models …
food security. The recent revolution in smartphone penetration and computer vision models …
Advances in vegetation map** through remote sensing and machine learning techniques: a scientometric review
C Matyukira, P Mhangara - European Journal of Remote Sensing, 2024 - Taylor & Francis
This study explores the rapid growth in remote-sensing technologies for vegetation
map**, driven by the integration of advanced machine learning techniques. An analysis of …
map**, driven by the integration of advanced machine learning techniques. An analysis of …
[HTML][HTML] A convolutional neural networks based method for anthracnose infected walnut tree leaves identification
A Anagnostis, G Asiminari, E Papageorgiou… - Applied Sciences, 2020 - mdpi.com
Anthracnose is a fungal disease that infects a large number of trees worldwide, damages
intensively the canopy, and spreads with ease to neighboring trees, resulting in the potential …
intensively the canopy, and spreads with ease to neighboring trees, resulting in the potential …
A deep learning framework for target localization in error-prone environment
The use of Internet of Things (IoT) in environment monitoring has led to the development of
Smart Environmental Monitoring (SEM) paradigm. Target or source localization, that …
Smart Environmental Monitoring (SEM) paradigm. Target or source localization, that …