[HTML][HTML] Advancements in maize disease detection: A comprehensive review of convolutional neural networks
B Gülmez - Computers in Biology and Medicine, 2024 - Elsevier
This review article provides a comprehensive examination of the state-of-the-art in maize
disease detection leveraging Convolutional Neural Networks (CNNs). Beginning with the …
disease detection leveraging Convolutional Neural Networks (CNNs). Beginning with the …
[HTML][HTML] Enabling Intelligence on the Edge: Leveraging Edge Impulse to Deploy Multiple Deep Learning Models on Edge Devices for Tomato Leaf Disease Detection
DAN Gookyi, FA Wulnye, M Wilson, P Danquah… - AgriEngineering, 2024 - mdpi.com
Tomato diseases, including Leaf blight, Leaf curl, Septoria leaf spot, and Verticillium wilt, are
responsible for up to 50% of annual yield loss, significantly impacting global tomato …
responsible for up to 50% of annual yield loss, significantly impacting global tomato …
Power Efficient Non-Mechanical Weather Station: Harnessing TinyML for Rainfall Classification and Environmental Sensing
DAN Gookyi, FA Wulnye… - 2024 IEEE 9th …, 2024 - ieeexplore.ieee.org
In response to the pressing need for accurate and cost-effective weather monitoring in
agricultural settings, this paper presents a next-generation Tiny Machine Learning (TinyML) …
agricultural settings, this paper presents a next-generation Tiny Machine Learning (TinyML) …
[PDF][PDF] Adaptive Learning Ability Enhancing of The Slow Sensor: A Machine Learning Approach
S Xu, TW Chang, YS Wu - 2024 - preprints.org
Slow sensors, widely used in industrial automation, environmental monitoring, and smart
agriculture, face significant challenges in real-time data processing due to limitations such …
agriculture, face significant challenges in real-time data processing due to limitations such …
[PDF][PDF] Integrated Thermal Monitoring System for Solar PV Panels: An Approach Based on TinyML and Edge Computing
AD Suárez-Gómez, JOB Quintero - 2024 - ceur-ws.org
This paper presents an integrated system for thermal monitoring and anomaly detection of
solar pv panels using TinyML and Edge Computing. The proposed system employs a low …
solar pv panels using TinyML and Edge Computing. The proposed system employs a low …
[引用][C] An unsupervised tinyML incremental learning approach for outlier processing and forecasting
PHM Andrade - 2024 - … Federal do Rio Grande do Norte