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Convolutional Neural Networks-Based Approach to Detect Neonatal Respiratory System Anomalies with Limited Thermal Image

Saim Ervural, Murat Ceylan
2021 Traitement du signal  
Convolutional neural network (CNN) models, although a powerful classification tool, require a balanced and large amount of data.  ...  Thermal imaging stands out as a harmless non-ionizing method, and monitoring of temperature changes or thermal symmetry is used as a diagnostic tool in medicine.  ...  Softmax operate generates probability-based loss value by exploitation score values created by artificial neural network.  ... 
doi:10.18280/ts.380222 fatcat:j5yau7m4ynbnvbtkepyntzsxbi

A Potential Method for the Nonuniformity Correction and Noise Removal of Infrared Thermal Image

Xiangyu Zeng, Jun Xu, Xiumin Gao
2020 Acta Physica Polonica. A  
A method for the nonuniformity correction and noise removal of the infrared thermal images that combines convolutional neural networks with a double-Gaussian filter was proposed.  ...  So, combined convolutional neural networks with a double-Gaussian filter may be a potential method for the nonuniformity correction and denoising of the infrared thermal image.  ...  A convolutional neural network combined with double-gaussian filter for noise removal and nonuniformity correction for the infrared images was proposed. (1055) 2.  ... 
doi:10.12693/aphyspola.137.1055 fatcat:q5ne75z7hvgefanth6decgbmge

THERMALNET: A DEEP CONVOLUTIONAL NETWORK FOR SYNTHETIC THERMAL IMAGE GENERATION

V. V. Kniaz, V. S. Gorbatsevich, V. A. Mizginov
2017 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images.  ...  Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms.  ...  Examples of generated images CONCLUSION A deep convolutional network for synthetic thermal image generation was developed. The network is based on the SqueezeNet deep convolutional network.  ... 
doi:10.5194/isprs-archives-xlii-2-w4-41-2017 fatcat:knijaes4lvhmfablsthuqovsd4

Multi-Scale Ensemble Learning for Thermal Image Enhancement

Yuseok Ban, Kyungjae Lee
2021 Applied Sciences  
In this study, we propose a multi-scale ensemble learning method for thermal image enhancement in different image scale conditions based on convolutional neural networks.  ...  Incorporating the multiple scales of thermal images has been a tricky task so that methods have been individually trained and evaluated for each scale.  ...  [11] presented a residual network for thermal image enhancement. They experimentally verified that the brightness domain is best suited for training a network for thermal image enhancement.  ... 
doi:10.3390/app11062810 fatcat:2522wjrkabffbfkqf44n4vdh7u

Paddy Leaf diseases identification on Infrared Images based on Convolutional Neural Networks [article]

Petchiammal A, Briskline Kiruba S, D. Murugan
2022 arXiv   pre-print
This paper implements a convolutional neural network (CNN) based on a model and tests a public dataset consisting of 636 infrared image samples with five paddy disease classes and one healthy class.  ...  Agriculture is the mainstay of human society because it is an essential need for every organism.  ...  This paper developed a Convolutional Neural Network (CNN) based classification model for identifying rice disease.  ... 
arXiv:2208.00031v2 fatcat:d6ens7cawjfmrnz6b3lnb3dht4

FLGC-Fusion GAN: An Enhanced Fusion GAN Model by Importing Fully Learnable Group Convolution

C. Yuan, C. Q. Sun, X. Y. Tang, R. F. Liu, Xiaojie Guo
2020 Mathematical Problems in Engineering  
To this end, we propose a new end-to-end network structure based on generative adversarial networks (GANs), termed as FLGC-Fusion GAN.  ...  Fusion GAN has made a breakthrough in this field by proposing to use the generative adversarial network to fuse images.  ...  e architecture of each part is based on a learnable grouping convolutional neural network.  ... 
doi:10.1155/2020/6384831 fatcat:esiaqe2ghrb25lxecmymp3wmae

Front Matter: Volume 11041

Jianhong Zhou, Antanas Verikas, Petia Radeva, Dmitry P. Nikolaev
2019 Eleventh International Conference on Machine Vision (ICMV 2018)  
learning; deep neural networks; and convolutional neural networks.  ...  Cloud Chaser: real time deep learning computer vision on low computing power devices [11041-82] 11041 2R Wavelet based edge feature enhancement for convolutional neural networks [11041-39] 11041  ... 
doi:10.1117/12.2532275 dblp:conf/icmv/X18 fatcat:hagr7bduabfjjbcj6acuuuswti

Real-Time Identification of Nonstandard Thermal Inkjet Codes on the Surface of Hot-Rolled Steel Sheets in Complex Environments

Xing-Hua Wang, Le Liang, Hong-Wei Sun, Wei-Bin Chen, Can-Can Wang, Yang-Yang Sun, A. Parthiban
2022 Advances in Materials Science and Engineering  
In this paper, a lightweight YOLO with ResNet18 as the backbone network is used as the detection and recognition framework, and deformable convolution and text feature extraction techniques are purposefully  ...  added to detect the location of thermal inkjet codes images to achieve accurate and fast positioning and segmentation of thermal spray codes.  ...  factors, resulting in the brightness or darkness of the image. erefore, it is necessary to preprocess the actual captured global image of the thermal inkjet code, and this paper uses contrast enhancement  ... 
doi:10.1155/2022/2620316 fatcat:s2i23nqfrjfg7n2c4ubdq7bcdi

Information Fusion of Infrared Images and Vibration Signals for Coupling Fault Diagnosis of Rotating Machinery

Tangbo Bai, Jianwei Yang, Dechen Yao, Ying Wang, Huaitao Shi
2021 Shock and Vibration  
Then, a multichannel convolution neural network-based method is constructed to achieve data-level information fusion and improve the fault diagnosis accuracy.  ...  Firstly, data enhancement for infrared images and data visualization for vibration are performed on the dataset by using the principle of graphics and Short-Term Fourier Transform, which increases the  ...  Figure 1 :Figure 2 : 12 Figure 1: Structure of convolutional neural network for RGB image. Figure 3 : 3 Figure 3: Infrared image enhancement. (a) Original. (b) Rotating. (c) Scaling.  ... 
doi:10.1155/2021/6622041 fatcat:dsxckpsix5ba7m7ge6aqkcjmpy

HUMAN DETECTION BASED ON A SEQUENCE OF THERMAL IMAGES USING DEEP LEARNING

X. Wang, S. Hosseinyalamdary
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
</p><p>Compared with the traditional method, the deep learning neural network has the advantages of shorter computing time, higher accuracy and easier operation.  ...  Human detection is a still challenging task because, for the group of people, each individual has his unique appearance and, body shape.  ...  Here, I propose a novel idea to add temporal information to the thermal images and apply Temporal convolutional neural network (T-CNN).  ... 
doi:10.5194/isprs-archives-xlii-2-w13-127-2019 fatcat:hqpnjgdt6fcddhbaetmatnmahu

CIM-Based Smart Pose Detection Sensors

Jyun-Jhe Chou, Ting-Wei Chang, Xin-You Liu, Tsung-Yen Wu, Yu-Kai Chen, Ying-Tuan Hsu, Chih-Wei Chen, Tsung-Te Liu, Chi-Sheng Shih
2022 Sensors  
Several new sensing algorithms use deep neural network algorithms and consume even more computation resources.  ...  This work designs and evaluates the CIM-based sensing framework for human pose recognition.  ...  It can be used to enhance the resource use of conducting neural network based algorithms. CIM chips usually consist of three parts.  ... 
doi:10.3390/s22093491 pmid:35591180 pmcid:PMC9102820 fatcat:a2jwvxgdcrf7ta2rpizhk2cswa

Review on Infrared Imaging Technology

Fujin Hou, Yan Zhang, Yong Zhou, Mei Zhang, Bin Lv, Jianqing Wu
2022 Sustainability  
, and image pseudo color enhancement of infrared thermal imagers, and briefly analyzes some main algorithms used in image processing.  ...  By reviewing the development of infrared thermal imagers, this paper introduces several main processing technologies of infrared thermal imagers, expounds the image nonuniformity correction, noise removal  ...  Deep learning algorithms mainly include infrared image enhancement algorithms based on convolutional neural networks and human visual characteristics.  ... 
doi:10.3390/su141811161 fatcat:rsghmkpjh5cffk7dlshf6mmkjq

Deep Neural Networks for Pattern Recognition [article]

Kyongsik Yun, Alexander Huyen, Thomas Lu
2018 arXiv   pre-print
Finally, recent developments in training strategies for effective learning of complex deep neural networks are addressed.  ...  Deep neural networks simulate the human visual system and achieve human equivalent accuracy in image classification, object detection, and segmentation.  ...  CONCLUSION Deep convolutional neural networks, especially conditional generative adversarial networks tremendously improved the accuracy in image classification and enhancement, and object detection and  ... 
arXiv:1809.09645v1 fatcat:lmtonzgfkrcrte3vglkfl6cbw4

Swin-MFA: A Multi-Modal Fusion Attention Network Based on Swin-Transformer for Low-Light Image Human Segmentation

Xunpeng Yi, Haonan Zhang, Yibo Wang, Shujiang Guo, Jingyi Wu, Cien Fan
2022 Sensors  
The encoder, which contains a two-branch swin-transformer backbone instead of the traditional convolutional neural network, fuses the RGB and depth features with a multiscale fusion attention block.  ...  In recent years, image segmentation based on deep learning has been widely used in medical imaging, automatic driving, monitoring and security.  ...  Starting from the proposal of a fully convolutional neural network (FCN) [7] , semantic segmentation algorithms based on neural networks have appeared on the stage.  ... 
doi:10.3390/s22166229 pmid:36015990 pmcid:PMC9413725 fatcat:3o5n7b6jbjdznncp3eyx6ysosy

Cloud detection methodologies: variants and development—a review

Seema Mahajan, Bhavin Fataniya
2019 Complex & Intelligent Systems  
Authors of [9] experimented through a convolutional neural network (CNN) and deep forest. They have used a segmented super pixel level of remote-sensing image database.  ...  An automatic cloud detection algorithm based on the spatial texture analysis and neural network is used in Ref. [8].  ...  classification, random forest-based methods, object-based convolution neural network, etc.  ... 
doi:10.1007/s40747-019-00128-0 fatcat:ftol5w36vzdwzpuqeijsz2dct4
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