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[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 …
NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data
Brain tumors (BTs) are one of the deadliest diseases that can significantly shorten a person's
life. In recent years, deep learning has become increasingly popular for detecting and …
life. In recent years, deep learning has become increasingly popular for detecting and …
[HTML][HTML] SBXception: a shallower and broader xception architecture for efficient classification of skin lesions
Simple Summary Skin cancer is a major concern worldwide, and accurately identifying it is
crucial for effective treatment. we propose a modified deep learning model called …
crucial for effective treatment. we propose a modified deep learning model called …
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 …
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 …
Advances in the use of deep learning for the analysis of magnetic resonance image in neuro-oncology
Simple Summary Within the rapidly evolving landscape of Machine Learning in the medical
field, this paper focuses on the forefront advancements in neuro-oncological radiology. More …
field, this paper focuses on the forefront advancements in neuro-oncological radiology. More …
Improved multiclass brain tumor detection via customized pretrained EfficientNetB7 model
A brain tumor considered the deadliest disease in the world. Patients with misdiagnoses and
insufficient treatment have a lower chance of surviving for life. However, for diagnosing the …
insufficient treatment have a lower chance of surviving for life. However, for diagnosing the …
[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] An intelligent attention-based transfer learning model for accurate differentiation of bone marrow stains to diagnose hematological disorder
Bone marrow (BM) is an essential part of the hematopoietic system, which generates all of
the body's blood cells and maintains the body's overall health and immune system. The …
the body's blood cells and maintains the body's overall health and immune system. The …