Texture defect classification with multiple pooling and filter ensemble based on deep neural network
Fabric quality control is one of the most important phases of production in order to ensure
high-quality standards in the fabric production sector. For this reason, the development of …
high-quality standards in the fabric production sector. For this reason, the development of …
[PDF][PDF] Fish species recognition using VGG16 deep convolutional neural network
P Hridayami, IKGD Putra, KS Wibawa - Journal of Computing Science …, 2019 - jcse.kiise.org
Conservation and protection of fish species is very important in aquaculture and marine
biology. A few studies have introduced the concept of fish recognition; however, it resulted in …
biology. A few studies have introduced the concept of fish recognition; however, it resulted in …
A novel pavement transverse cracks detection model using WT-CNN and STFT-CNN for smartphone data analysis
This paper proposes a novel pavement transverse crack detection model based on time–
frequency analysis and convolutional neural networks. The accelerometer and smartphone …
frequency analysis and convolutional neural networks. The accelerometer and smartphone …
[PDF][PDF] Classification of rice plant diseases using the convolutional neural network method
A Priyangka, IMS Kumara - Lontar Komputer: Jurnal Ilmiah Teknologi …, 2021 - academia.edu
Indonesia is one of the countries with the population majority of farming. The agricultural
sector in Indonesia is supported by fertile land and a tropical climate. Rice is one of the …
sector in Indonesia is supported by fertile land and a tropical climate. Rice is one of the …
[HTML][HTML] Race estimation with deep networks
Identifying race, which is a major physical feature in humans, is still a challenging task owing
much to the lack of a concrete definition of race and the diversity of population across the …
much to the lack of a concrete definition of race and the diversity of population across the …
DepthCrackNet: A Deep Learning Model for Automatic Pavement Crack Detection
A Saberironaghi, J Ren - Journal of Imaging, 2024 - mdpi.com
Detecting cracks in the pavement is a vital component of ensuring road safety. Since manual
identification of these cracks can be time-consuming, an automated method is needed to …
identification of these cracks can be time-consuming, an automated method is needed to …
Enhanced Disease Detection in Pomegranate Cultivation Using PF-CNN: A Deep Learning Approach for Improved Yield and Quality Management
Fruit cultivation is a key contributor to the agricultural economy, with pomegranate being
particularly valued for its high nutritional content, including antioxidants, vitamins, and fiber …
particularly valued for its high nutritional content, including antioxidants, vitamins, and fiber …
Multimodal Biometric Recognition System Based on Residual Neural Network-101
AK Gona, M Subramoniam, R Swarnalatha - Available at SSRN 4241184 - papers.ssrn.com
In past decades, for the purpose of security Biometric system is used worldwide. However,
unimodal biometrics have some constrains and weakness and it also suffers from spoof …
unimodal biometrics have some constrains and weakness and it also suffers from spoof …
Evaluation of Deep Learning Models in the Prediction of Lung Disease (Pneumonia)
A Rohit, B Padmaja, K Vinay Kumar… - Data Intelligence and …, 2021 - Springer
Medical diagnosis is one of the fields in which there is a great scope for deep neural
networks. Pneumonia is a severe infectious disease that can be predicted using chest x-rays …
networks. Pneumonia is a severe infectious disease that can be predicted using chest x-rays …
[PDF][PDF] Computer and Information Sciences
S Ma, H Liu, N Pan, S Wang - Journal of King Saud University …, 2023 - researchgate.net
abstract Unmanned aerial vehicles (UAVs) have attracted much attention for civil and
military uses because of their high mobility and adaptable deployment capabilities in open …
military uses because of their high mobility and adaptable deployment capabilities in open …