[HTML][HTML] Harnessing the power of transfer learning in sunflower disease detection: A comparative study

Y Gulzar, Z Ünal, H Aktaş, MS Mir - Agriculture, 2023 - mdpi.com
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 …

NeuroNet19: an explainable deep neural network model for the classification of brain tumors using magnetic resonance imaging data

R Haque, MM Hassan, AK Bairagi, SM Shariful Islam - Scientific reports, 2024 - nature.com
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 …

[HTML][HTML] SBXception: a shallower and broader xception architecture for efficient classification of skin lesions

A Mehmood, Y Gulzar, QM Ilyas, A Jabbari, M Ahmad… - Cancers, 2023 - mdpi.com
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 …

Adaptability of deep learning: datasets and strategies in fruit classification

Y Gulzar, Z Ünal, S Ayoub, FA Reegu… - BIO Web of …, 2024 - bio-conferences.org
This review aims to uncover the multifaceted landscape of methodologies employed by
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 …

Advances in the use of deep learning for the analysis of magnetic resonance image in neuro-oncology

C Pitarch, G Ungan, M Julià-Sapé, A Vellido - Cancers, 2024 - mdpi.com
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 …

Improved multiclass brain tumor detection via customized pretrained EfficientNetB7 model

HMT Khushi, T Masood, A Jaffar, M Rashid… - IEEE …, 2023 - ieeexplore.ieee.org
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 …

[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 …

I Malik, M Ahmed, Y Gulzar, SH Baba, MS Mir… - Sustainability, 2023 - mdpi.com
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 …

[PDF][PDF] Enhanced transfer learning strategies for effective kidney tumor classification with CT imaging

M Majid, Y Gulzar, S Ayoub, F Khan… - International …, 2023 - pdfs.semanticscholar.org
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 …

[HTML][HTML] An intelligent attention-based transfer learning model for accurate differentiation of bone marrow stains to diagnose hematological disorder

H Alshahrani, G Sharma, V Anand, S Gupta… - Life, 2023 - mdpi.com
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 …