[HTML][HTML] Fruit image classification model based on MobileNetV2 with deep transfer learning technique
Y Gulzar - Sustainability, 2023 - mdpi.com
Due to the rapid emergence and evolution of AI applications, the utilization of smart imaging
devices has increased significantly. Researchers have started using deep learning models …
devices has increased significantly. Researchers have started using deep learning models …
[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] 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 …
[HTML][HTML] Generating image captions using Bahdanau attention mechanism and transfer learning
Automatic image caption prediction is a challenging task in natural language processing.
Most of the researchers have used the convolutional neural network as an encoder and …
Most of the researchers have used the convolutional neural network as an encoder and …
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 …
[HTML][HTML] Enhanced corn seed disease classification: Leveraging MobileNetV2 with feature augmentation and transfer learning
M Alkanan, Y Gulzar - Frontiers in Applied Mathematics and Statistics, 2024 - frontiersin.org
In the era of advancing artificial intelligence (AI), its application in agriculture has become
increasingly pivotal. This study explores the integration of AI for the discriminative …
increasingly pivotal. This study explores the integration of AI for the discriminative …
[HTML][HTML] Least square-support vector machine based brain tumor classification system with multi model texture features
Radiologists confront formidable challenges when confronted with the intricate task of
classifying brain tumors through the analysis of MRI images. Our forthcoming manuscript …
classifying brain tumors through the analysis of MRI images. Our forthcoming manuscript …
[PDF][PDF] Using ensemble learning and advanced data mining techniques to improve the diagnosis of chronic kidney disease
Kidney failure is a condition with far-reaching, potentially life-threatening consequences on
the human body. Leveraging the power of machine learning and data mining, this research …
the human body. Leveraging the power of machine learning and data mining, this research …