Brainnet: Precision brain tumor classification with optimized efficientnet architecture
Brain tumors significantly impact human health due to their complexity and the challenges in
early detection and treatment. Accurate diagnosis is crucial for effective intervention, but …
early detection and treatment. Accurate diagnosis is crucial for effective intervention, but …
Predicting and optimizing reactive oxygen species metabolism in Punica granatum L. through machine learning: role of exogenous GABA on antioxidant enzyme …
S Zarbakhsh, AR Shahsavar, A Afaghi… - BMC Plant …, 2024 - Springer
Background Drought and salinity stress have been proposed as the main environmental
factors threatening food security, as they adversely affect crops' agricultural productivity. As a …
factors threatening food security, as they adversely affect crops' agricultural productivity. As a …
[HTML][HTML] Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review
HN Ngugi, AA Akinyelu, AE Ezugwu - Agronomy, 2024 - mdpi.com
Crop diseases pose a significant threat to global food security, with both economic and
environmental consequences. Early and accurate detection is essential for timely …
environmental consequences. Early and accurate detection is essential for timely …
Brain tumor classification using fine-tuned transfer learning models on magnetic resonance imaging (MRI) images
Objective Brain tumors are a leading global cause of mortality, often leading to reduced life
expectancy and challenging recovery. Early detection significantly improves survival rates …
expectancy and challenging recovery. Early detection significantly improves survival rates …
[HTML][HTML] An ensemble machine learning based bank loan approval predictions system with a smart application
Banks rely heavily on loans as a primary source of revenue; however, distinguishing
deserving applicants who will reliably repay loans presents an ongoing challenge …
deserving applicants who will reliably repay loans presents an ongoing challenge …
Detection of plant leaf diseases using deep convolutional neural network models
P Singla, V Kalavakonda, R Senthil - Multimedia Tools and Applications, 2024 - Springer
Food demand is exponentially increasing due to the increase in population in every country;
hence, increasing the yield is one of the focus areas for sustainable agricultural …
hence, increasing the yield is one of the focus areas for sustainable agricultural …
Deep Learning based Models for Paddy Disease Identification and Classification: A Systematic Survey
Automated early detection and classification of paddy diseases help in applying treatment
efficiently according to the detected diseases. Early detection also minimises the usage of …
efficiently according to the detected diseases. Early detection also minimises the usage of …
Construction and validation of peanut leaf spot disease prediction model based on long time series data and deep learning
Z Guo, X Chen, M Li, Y Chi, D Shi - Agronomy, 2024 - mdpi.com
Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut
yield and quality, and accurate prediction models are urgently needed for timely disease …
yield and quality, and accurate prediction models are urgently needed for timely disease …
Deep-sdm: A unified computational framework for sequential data modeling using deep learning models
Deep-SDM is a unified layer framework built on TensorFlow/Keras and written in Python
3.12. The framework aligns with the modular engineering principles for the design and …
3.12. The framework aligns with the modular engineering principles for the design and …
Real-time disease detection on bean leaves from a small image dataset using data augmentation and deep learning methods
Disease detection in agricultural crops plays a pivotal role in ensuring food security and
sustainable farming practices. Deep learning models, known for their ability in image …
sustainable farming practices. Deep learning models, known for their ability in image …