[HTML][HTML] Image acquisition, preprocessing and classification of citrus fruit diseases: A systematic literature review
Different kinds of techniques are evaluated and analyzed for various classification models
for the detection of diseases of citrus fruits. This paper aims to systematically review the …
for the detection of diseases of citrus fruits. This paper aims to systematically review the …
[HTML][HTML] Harnessing the power of transfer learning in sunflower disease detection: A comparative study
Sunflower is an important crop that is susceptible to various diseases, which can
significantly impact crop yield and quality. Early and accurate detection of these diseases is …
significantly impact crop yield and quality. Early and accurate detection of these diseases is …
[HTML][HTML] Weighted average ensemble deep learning model for stratification of brain tumor in MRI images
Brain tumor diagnosis at an early stage can improve the chances of successful treatment
and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures …
and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures …
[HTML][HTML] Comparing inception V3, VGG 16, VGG 19, CNN, and ResNet 50: a case study on early detection of a rice disease
Rice production has faced numerous challenges in recent years, and traditional methods
are still being used to detect rice diseases. This research project developed an automated …
are still being used to detect rice diseases. This research project developed an automated …
[HTML][HTML] Detection and counting of small target apples under complicated environments by using improved YOLOv7-tiny
L Ma, L Zhao, Z Wang, J Zhang, G Chen - Agronomy, 2023 - mdpi.com
Weather disturbances, difficult backgrounds, the shading of fruit and foliage, and other
elements can significantly affect automated yield estimation and picking in small target apple …
elements can significantly affect automated yield estimation and picking in small target apple …
[HTML][HTML] Adversarial approaches to tackle imbalanced data in machine learning
Real-world applications often involve imbalanced datasets, which have different
distributions of examples across various classes. When building a system that requires a …
distributions of examples across various classes. When building a system that requires a …
Dynamic Economic Load Dispatch Problem in Power System Using Iterative Genetic Algorithm
The economic load dispatch and social security as its name implies requires that generating
units must be paired in order to optimize operating cost. In the power sector, the generating …
units must be paired in order to optimize operating cost. In the power sector, the generating …
Adaptability of deep learning: datasets and strategies in fruit classification
This review aims to uncover the multifaceted landscape of methodologies employed by
researchers for accurate fruit classification. The exploration encompasses an array of …
researchers for accurate fruit classification. The exploration encompasses an array of …
[HTML][HTML] Estimation of the extent of the vulnerability of agriculture to climate change using analytical and deep-learning methods: a case study in Jammu, Kashmir, and …
Climate stress poses a threat to the agricultural sector, which is vital for both the economy
and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability …
and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability …
[PDF][PDF] Enhanced transfer learning strategies for effective kidney tumor classification with CT imaging
Kidney tumours (KTs) rank seventh in global tumour prevalence among both males and
females, posing a significant health challenge worldwide. Early detection of KT plays a …
females, posing a significant health challenge worldwide. Early detection of KT plays a …