Results 71 to 80 of about 17,494 (194)

FACE RECOGNITION USING DEEP LEARNING XCEPTION CNN METHOD

, 2022
The continual development of computer vision technology is one of the main research paths in the area of computer vision during recent years. It detects, tracks, recognizes, or authenticates human appearances from any picture or video taken through a digital camera and provides accurate and quick enough recognition functions for commercial use.
PALLAVARAM VENKATESWAR LAL, UPPALAPATI SRILAKSHMI, D.VENKATESWARLU   +2 more
openaire   +1 more source

A new architecture based on the Xception algorithm for pneumonia detection using medical image datasets

Computer Methods and Programs in Biomedicine Update
This study aims to improve the reliability of pneumonia detection from chest X-ray images by addressing the instability and performance variability observed in conventional CNNs, particularly the original Xception architecture, under different training ...
Chaymae Taib, Otman Abdoun, El Khatir Haimoudi   +2 more
doaj   +1 more source

Improved CBAM Rock Image Classification Based on Xception

, 2023
To address the problems of traditional machine learning algorithms in rock recognition which are time-consuming, labor-intensive and low accuracy, a migration learning method using network weights for feature learning based on Xception network structure and incorporating an improved convolutional attention module (CBAM) to strengthen the important ...
Zhang, Tingting, Ren, Shuyan, Duan, Hailong, Wen, Shuoyi   +3 more
openaire   +1 more source

Application of deep learning in damage classification of reinforced concrete bridges

Ain Shams Engineering Journal
Inspecting Reinforced Concrete (RC) Bridges is crucial to ensure their safety and perform essential maintenance. The current research introduces the knowledge base for applying deep learning to classify and detect RC bridges' five most common defects ...
Mustafa Abubakr, Mohammed Rady, Khaled Badran, Sameh Youssef Mahfouz   +3 more
doaj   +1 more source

Transfer Learning Model Application for Rastrelliger brachysoma and R. kanagurta Image Classification Using Smartphone-Captured Images

Fishes
Prior aquatic animal image classification research focused on distinguishing external features in controlled settings, utilizing either digital cameras or webcams.
Roongparit Jongjaraunsuk, Wara Taparhudee, Soranuth Sirisuay, Methee Kaewnern, Varunthat Dulyapurk, Sommai Janekitkarn   +5 more
doaj   +1 more source

Prediction of Vehicle Interior Wind Noise Based on Shape Features Using the WOA-Xception Model

Machines
In order to confront the challenge of efficiently evaluating interior wind noise levels in passenger vehicles during the early stages of shape design, this paper proposes a methodology for predicting interior wind noise.
Yan Ma, Hongwei Yi, Long Ma, Yuwei Deng, Jifeng Wang, Yudong Wu, Yuming Peng   +6 more
doaj   +1 more source

Use of Xception Architecture for the Classification of Skin Lesions [PDF]

Journal of Systemics, Cybernetics and Informatics
This study investigates the application of the Xception architecture for accurate classification of skin lesions, focusing on the early detection of melanoma and other malignant skin conditions.
Cledmir Tejada, Gustavo Espinoza, Daniel Subauste   +2 more
doaj  

Brain tumor classification using a hybrid ensemble of Xception and parallel deep CNN models

Informatics in Medicine Unlocked
Objective: Accurate classification of brain tumors is essential for effective diagnosis and treatment planning. The purpose of this study is to develop and evaluate a hybrid ensemble brain tumor classification method to leverage the strengths of two ...
Seoyoung Yoon
doaj   +1 more source

Adjusting Xception Neural Network by Improved Human Evolutionary Optimizer for Fine Art Sorting

IEEE Access
This study tackles the problem of fine-art image classification that suffers from both the softness of styles and the absence of labelled datasets. The state-of-the-art with CNNs leverages transfer learning and fine-tuning to overcome the scarcity of ...
Tianfu Liu
doaj   +1 more source

Comparative Analysis of Transfer Learning, LeafNet, and Modified LeafNet Models for Accurate Rice Leaf Diseases Classification

IEEE Access
Early detection of plant diseases is essential for effective crop disease management to prevent yield loss. In this study, we developed a methodology for classifying diseases in rice leaves using four deep learning models and a dataset with 2658 images ...
Wassem I. A. E. Altabaji, Muhammad Umair, Wooi-Haw Tan, Yee-Loo Foo, Chee-Pun Ooi   +4 more
doaj   +1 more source