Results 41 to 50 of about 12,736 (188)
Klasifikasi Rhinosinusitis Menggunakan Modifikasi VGG16
Rhinosinusitis is an inflammatory disease affecting the mucosal lining of the nasal cavity (rhinitis) and paranasal sinuses (sinusitis), posing a significant public health challenge in Indonesia due to its high clinical and economic burden. This study aims to develop an advanced diagnostic method to assist healthcare professionals in accurately ...
Thia Anissa +2 more
openaire +1 more source
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam +3 more
wiley +1 more source
Transfer learning pada Network VGG16 dan ResNet50
Transfer Learning adalah prinsip yang digunakan pada neural network dengan tujuan membantu pelatihan pada data yang sedikit, mempercepat waktu dan meningkatkan performa pelatihan. Salah satu metode transfer learning adlaah fine tuning. Pada metode tersebut, melakukan pembekuan pada sejumlah layer pada model network yang dilatih sebelumnya dan melakukan
null Fauzan Muhammad +2 more
openaire +1 more source
Enhancing Generalisation via Cascaded Inertia SGD With Learnt Hyperparameters
ABSTRACT A central challenge in deep learning lies in achieving strong model generalisation, an area in which conventional optimisers such as stochastic gradient descent (SGD) often exhibit limitations, even though they ensure convergence. This paper introduces cascaded inertia SGD (CISGD), a novel optimisation algorithm specifically designed to ...
Yongji Guan +3 more
wiley +1 more source
ABSTRACT Generalisation is a crucial aspect of deep learning, enabling models to perform well on unseen data. Currently, most optimisers that improve generalisation typically suffer from efficiency bottlenecks. This paper proposes a double‐integration‐enhanced stochastic gradient descent (DIESGD) optimiser, which treats the negative gradient as an ...
Ting Li +3 more
wiley +1 more source
Using Deep Learning for Image-Based Different Degrees of Ginkgo Leaf Disease Classification
Diseases from Ginkgo biloba have brought great losses to medicine and the economy. Therefore, if the degree of disease can be automatically identified in Ginkgo biloba leaves, people will take appropriate measures to avoid losses in advance.
Kaizhou Li +3 more
doaj +1 more source
Textile and colour defect detection using deep learning methods
Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui +2 more
wiley +1 more source
A Deep Learning Approach Using VGG16 to Classify Beef and Pork Images
There are 87.2% of the Muslim population in Indonesia, which makes Indonesia one of the countries with the largest Muslim population in the world. As a Muslim, it is supposed to carry out and stay away from the commands that Allah SWT commands, one of ...
Wildan Budiawan Zulfikar +4 more
doaj +1 more source
KLASIFIKASI KONDISI BAN KENDARAAN MENGGUNAKAN ARSITEKTUR VGG16
Tyres are the main component that a vehicle needs to work with reducing vibration due to uneven road surfaces, protecting the wheels from wear to provide stability between the vehicle and the ground helping to improve acceleration to facilitate travel while driving.
Teguh Iman Hermanto +2 more
openaire +1 more source
ABSTRACT Aim Artificial intelligence (AI) has the potential to aid clinicians in assessing case difficulty in endodontics. The objectives of this study were to develop and validate deep learning models for the detection of clinically negotiable MB2 canals in periapical images of maxillary first and second molars, and to compare the performance of AI ...
Seyed AmirHossein Ourang +8 more
wiley +1 more source

