Results 21 to 30 of about 12,736 (188)

ENHANCING DISEASE DETECTION PREDICTION ACCURACY OF GRAPE LEAVES USING VGG16 MODEL AND INCEPTION V3 MODEL [PDF]

Proceedings on Engineering Sciences
Plant diseases can impact the leaves at any point from sowing to harvesting, resulting in significant losses in crop production and market economic value.
Deepshikha Yadav , Archana Balyan , Suman Mann , Aayush Ranga   +3 more
doaj   +1 more source

Enhanced Melanoma Classifier with VGG16-CNN [PDF]

, 2021
Melanoma is the most severe kind of skin cancer that is becoming more common in the Western world. This is still thought to be caused primarily by exposure to the sun. Patients with malignant melanoma have a wide range of prognoses; however public awareness initiatives encouraging early detection have resulted in considerable reductions in mortality ...
openaire   +1 more source

Residual Squeeze VGG16

, 2017
Deep learning has given way to a new era of machine learning, apart from computer vision. Convolutional neural networks have been implemented in image classification, segmentation and object detection. Despite recent advancements, we are still in the very early stages and have yet to settle on best practices for network architecture in terms of deep ...
Qassim, Hussam, Feinzimer, David, Verma, Abhishek   +2 more
openaire   +2 more sources

Optimizing VGG16 Architecture with Bayesian Hyperparameter Tuning for Tomato Leaf Disease Classification

Jurnal Masyarakat Informatika
This study proposes an optimized VGG16 architecture enhanced through Bayesian Optimization to improve the classification of tomato leaf diseases. The modified model integrates tunable parameters such as dropout rates, convolutional filters, and dense ...
Tsaqif Muhammad Arkan, Aris Sugiharto, Helmie Arif Wibawa   +2 more
doaj   +1 more source

Comparison Study of Convolutional Neural Network Architecture in Aglaonema Classification

International Journal of Electronics and Communications System, 2022
Convolutional Neural Network (CNN) is very good at classifying images. To measure the best CNN architecture, a study must be done against real-case scenarios.
Yessi Mulyani, Dzihan Septiangraini, Meizano Ardhi Muhammad, Gigih Forda Nama   +3 more
doaj   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni, Md. Alif Sheakh, Mst. Sazia Tahosin, Md. Zahid Hasan, Taslima Ferdaus Shuva, Touhid Bhuiyan, Muhammad Ali Abdullah Almoyad, Nabil Anan Orka, Md. Tanvir Rahman, Risala Tasin Khan, M. Shamim Kaiser, Mohammad Ali Moni   +11 more
wiley   +1 more source

Application of VGG16 in Automated Detection of Bone Fractures in X-Ray Images

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
The purpose of this research is to determine whether or not a deep learning model called VGG16 can automatically identify bone fractures in X-ray pictures.
Resky Adhyaksa, Bedy Purnama
doaj   +1 more source

Deep Learning Approaches for Classifying Crack States With Overload and Predicting Fatigue Parameters in a Titanium Alloy

Advanced Intelligent Systems, EarlyView.
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi, Suman Timilsina, Youn Woo Shin, Yong Nam Kwon, Kee‐Sun Sohn, Ji Sik Kim   +5 more
wiley   +1 more source

Incorporating Deep Learning into the Diagnosis of Banana Leaf Spot Diseases for the Protection of Banana Crops

Journal of Agricultural Sciences
Banana crops play a pivotal role in securing global food supplies and supporting economic stability. However, they are confronted with significant challenges stemming from a variety of diseases that not only diminish yields but also compromise the ...
Cihan Ünal
doaj   +1 more source

A Shallow Convolutional Learning Network for Classification of Cancers Based on Copy Number Variations

Sensors, 2019
Genomic copy number variations (CNVs) are among the most important structural variations. They are linked to several diseases and cancer types. Cancer is a leading cause of death worldwide.
Ahmad AlShibli, Hassan Mathkour
doaj   +1 more source