A multi-biometric iris recognition system based on a deep learning approach
AS Al-Waisy, R Qahwaji, S Ipson, S Al-Fahdawi… - Pattern Analysis and …, 2018 - Springer
Multimodal biometric systems have been widely applied in many real-world applications due
to its ability to deal with a number of significant limitations of unimodal biometric systems …
to its ability to deal with a number of significant limitations of unimodal biometric systems …
A review of texture classification methods and databases
In this survey, we present a review of methods and resources for texture recognition,
presenting the most common techniques that have been used in the recent decades, along …
presenting the most common techniques that have been used in the recent decades, along …
Writer-independent feature learning for offline signature verification using deep convolutional neural networks
Automatic Offline Handwritten Signature Verification has been researched over the last few
decades from several perspectives, using insights from graphology, computer vision, signal …
decades from several perspectives, using insights from graphology, computer vision, signal …
Transfer learning for automated optical inspection
S Kim, W Kim, YK Noh, FC Park - 2017 international joint …, 2017 - ieeexplore.ieee.org
One of the challenges in applying convolutional neural networks to automated optical
inspection is the lack of sufficient training data. In this paper we show that transfer learning …
inspection is the lack of sufficient training data. In this paper we show that transfer learning …
Efficient neural network compression via transfer learning for machine vision inspection
S Kim, YK Noh, FC Park - Neurocomputing, 2020 - Elsevier
Several practical difficulties arise when trying to apply deep learning to image-based
industrial inspection tasks: training datasets are difficult to obtain, each image must be …
industrial inspection tasks: training datasets are difficult to obtain, each image must be …
Surface defects detection based on adaptive multiscale image collection and convolutional neural networks
Surface flaw inspection is of great importance for quality control in the field of manufacture.
In this paper, a novel surface flaw inspection algorithm is proposed based on adaptive …
In this paper, a novel surface flaw inspection algorithm is proposed based on adaptive …
Assessment of forest cover changes using multi-temporal Landsat observation
E Moradi, A Sharifi - Environment, Development and Sustainability, 2023 - Springer
Monitoring the changes in forest cover has become an important tool for forest management
due to its impact on climate change, desertification, soil erosion, and flooding. The Zagros …
due to its impact on climate change, desertification, soil erosion, and flooding. The Zagros …
Sensitive deep convolutional neural network for face recognition at large standoffs with small dataset
In this paper, we propose a sensitive convolutional neural network which incorporates
sensitivity term in the cost function of Convolutional Neural Network (CNN) to emphasize on …
sensitivity term in the cost function of Convolutional Neural Network (CNN) to emphasize on …
Deep learning in texture analysis and its application to tissue image classification
V Andrearczyk, PF Whelan - Biomedical texture analysis, 2017 - Elsevier
In the last decade, artificial intelligence has been revolutionized by deep learning,
outperforming human prediction on a wide range of problems. In particular Convolutional …
outperforming human prediction on a wide range of problems. In particular Convolutional …
An Inexactly Supervised Methodology Based on Multiple Instance Learning, Convolutional Neural Networks and Dissimilarities for Interpretable Defect Detection and …
E Villegas-Jaramillo, M Orozco-Alzate - IEEE Access, 2023 - ieeexplore.ieee.org
The detection, localization, and interpretation of defects in textured surfaces pose
challenges for automatic visual inspection. Both fully-supervised and weakly-supervised …
challenges for automatic visual inspection. Both fully-supervised and weakly-supervised …