A deep transfer learning based convolution neural network framework for air temperature classification using human clothing images
文献类型：期刊论文
| 作者 | Ahmed, Maqsood12; Zhang, Xiang11,12; Shen, Yonglin11; Ali, Nafees9,10; Flah, Aymen1,4,5,6,7,8; Kanan, Mohammad3; Alsharef, Mohammad2; Ghoneim, Sherif S. M.2 |
| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2024-12-30 |
| 卷号 | 14期号:1页码:17 |
| 关键词 | Air temperature Human clothing Deep transfer learning Classification |
| ISSN号 | 2045-2322 |
| DOI | 10.1038/s41598-024-80657-y |
| 英文摘要 | Weather recognition is crucial due to its significant impact on various aspects of daily life, such as weather prediction, environmental monitoring, tourism, and energy production. Several studies have already conducted research on image-based weather recognition. However, previous studies have addressed few types of weather phenomena recognition from images with insufficient accuracy. In this paper, we propose a transfer learning CNN framework for classifying air temperature levels from human clothing images. The framework incorporates various deep transfer learning approaches, including DeepLabV3 Plus for semantic segmentation and others for classification such as BigTransfer (BiT), Vision Transformer (ViT), ResNet101, VGG16, VGG19, and DenseNet121. Meanwhile, we have collected a dataset called the Human Clothing Image Dataset (HCID), consisting of 10,000 images with two categories (High and Low air temperature). All the models were evaluated using various classification metrics, such as the confusion matrix, loss, precision, F1-score, recall, accuracy, and AUC-ROC. Additionally, we applied Gradient-weighted Class Activation Mapping (Grad-CAM) to emphasize significant features and regions identified by models during the classification process. The results show that DenseNet121 outperformed other models with an accuracy of 98.13%. Promising experimental results highlight the potential benefits of the proposed framework for detecting air temperature levels, aiding in weather prediction and environmental monitoring. |
| 资助项目 | European Union under the REFRESH - Research Excellence for Region Sustainability and High-tech Industries via Operational Programme Just Transition[CZ.10.03.01/00/22_003/0000048] ; National Centre for Energy II and ExPEDite project a Research and Innovation action to support the implementation of the Climate Neutral and Smart Cities Mission projec[TN02000025] ; European Union's Horizon Mission Programme[101139527] ; Taif University, Saudi Arabia[TU-DSPP-2024-70] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001389338200014 |
| 出版者 | NATURE PORTFOLIO |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/37660]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Zhang, Xiang |
| 作者单位 | 1.Univ Business & Technol UBT, Coll Engn, Jeddah 21448, Saudi Arabia 2.Taif Univ, Coll Sci, Dept Biol, POB 11099, Taif 21944, Saudi Arabia 3.Univ Business & Technol UBT, Coll Engn, Ind Engn Dept, Jeddah 21448, Saudi Arabia 4.VSB Tech Univ Ostrava, Ostrava, Czech Republic 5.Appl Sci Private Univ, Appl Sci Res Ctr, Amman 11931, Jordan 6.Chitkara Univ, Chitkara Ctr Res & Dev, Baddi 174103, Himachal Prades, India 7.Chitkara Univ, Inst Engn & Technol, Ctr Res Impact & Outcome, Rajpura 140401, Punjab, India 8.Univ Gabes, Natl Engn Sch Gabes, Gabes 6072, Tunisia 9.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 10.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ahmed, Maqsood,Zhang, Xiang,Shen, Yonglin,et al. A deep transfer learning based convolution neural network framework for air temperature classification using human clothing images[J]. SCIENTIFIC REPORTS,2024,14(1):17. |
| APA | Ahmed, Maqsood.,Zhang, Xiang.,Shen, Yonglin.,Ali, Nafees.,Flah, Aymen.,...&Ghoneim, Sherif S. M..(2024).A deep transfer learning based convolution neural network framework for air temperature classification using human clothing images.SCIENTIFIC REPORTS,14(1),17. |
| MLA | Ahmed, Maqsood,et al."A deep transfer learning based convolution neural network framework for air temperature classification using human clothing images".SCIENTIFIC REPORTS 14.1(2024):17. |
入库方式： OAI收割
来源：武汉岩土力学研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。