International Conference on Digital Image Processing最新文献_第6页

A sample diversity and identity consistency based cross-modality model for visible-infrared person re-identification 基于样本多样性和身份一致性的可见-红外人物再识别交叉模态模型

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2644355

Jia Sun, Yanfeng Li, Houjin Chen, Yahui Peng

引用次数: 1

Breast cancer detection from ultrasound images using attention U-nets model 利用注意U-nets模型从超声图像中检测乳腺癌

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2643599

M. Farooq, Zhaoxuan Gong, Yu Liu, Muhammad Zubair, Arslan Manzoor, Guodong Zhang

{"title":"Breast cancer detection from ultrasound images using attention U-nets model","authors":"M. Farooq, Zhaoxuan Gong, Yu Liu, Muhammad Zubair, Arslan Manzoor, Guodong Zhang","doi":"10.1117/12.2643599","DOIUrl":"https://doi.org/10.1117/12.2643599","url":null,"abstract":"Breast cancer is the most common form of invasive cancer in women. In recent years, it has become standard practise to perform breast mass evaluations using ultrasound (US) imaging. US can accurately distinguish between malignant and benign breast masses when used by skilled radiologists, as compared to other medical imaging modalities such as MRI. Human domain knowledge is difficult to incorporate into the diagnosis of breast tumours because it differs greatly from person to person in terms of shape, border, curve, intensity, and other commonly used medical priors. A deep learning model that incorporates visual saliency can now be used to segment breast tumours in ultrasound images. Radiologists use the term \"visual saliency,\" which refers to areas of an image that are more likely to be noticed. Features that prioritise spatial regions with high saliency levels are learned using the proposed method. According to validation results, tumours are more accurately identified in models that include attention layers than those without them. The salient attention model has the potential to improve medical image analysis accuracy and robustness by allowing deep learning architectures to incorporate task-specific knowledge. AUC-ROC plots show that our new model is more accurate in terms of IOU and AUC-ROC scores, dice score, precision, recall, and IOU.","PeriodicalId":314555,"journal":{"name":"International Conference on Digital Image Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129521701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Metrical age assessment using image analysis and artificial neural networks 基于图像分析和人工神经网络的测量年龄评估

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2643001

Maciej Zaborowicz, Katarzyna Zaborowicz, B. Biedziak

引用次数: 0

Low frequency ultra-wideband BSAR electromagnetic scattering characteristic 低频超宽带BSAR电磁散射特性

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2644365

Hongtu Xie, Xiao Hu, Xinqiao Jiang, Zhitao Wu, Jinfeng He, Kai Xie, Guoqian Wang

引用次数: 0

RSFS: A soft biometrics-based relative support features set for person verification RSFS:用于人员验证的基于软生物识别的相对支持特性集

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2644457

Bilal Hassan, E. Izquierdo

{"title":"RSFS: A soft biometrics-based relative support features set for person verification","authors":"Bilal Hassan, E. Izquierdo","doi":"10.1117/12.2644457","DOIUrl":"https://doi.org/10.1117/12.2644457","url":null,"abstract":"Generally, biometrics is gaining increased attention due to its application for secure and efficient verification – more specifically at border crossing points. Usually, there are many different types of biometrics associated with human body i.e., intrusive like finger prints etc. and non-intrusive, termed as soft biometrics. In order to make the concept of Smart Borders a reality, the non-intrusive soft biometrics are the baseline technology. One of biggest challenge in soft biometrics based verification is to find a highly related set of features from different modalities of human body – as there is large number such soft biometrics associated with human body. In fact, this is extremely useful to select only those soft biometrics which are supportive to each other and relevant to the problem domain. In our work, we thoroughly investigated one of the largest collection of soft biometrics and developed a multiple non-linear regression based framework for the selection of highly supportive and relevant soft biometrics. We used one of the largest dataset e.g., PETA and its annotation for the evaluation of our proposed model. The accuracy is reported in form of MAE and error distribution graphs for two global soft biometrics i.e., gender and age prediction.","PeriodicalId":314555,"journal":{"name":"International Conference on Digital Image Processing","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132708104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Temperature imaging network based on swin transformer for TDLAS tomography 基于swin变压器的TDLAS层析温度成像网络

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2643397

Jingjing Si, Aiting Wang, Yinbo Cheng

引用次数: 1

Video stabilization based on GMS and warping transform 基于GMS和翘曲变换的视频稳像

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2644293

Jiwen Liu, Qian Huang, Yiming Wang, Chuanxu Jiang, Mingzhou Shang

引用次数: 0

An one-dimensional signal based object detection network for apnea and hypopnea locating 基于一维信号的目标检测网络用于呼吸暂停和低呼吸定位

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2643701

Xian-Lung Tang, Liang Zhao, Yanping Shuai, Zhang Li, Xingjun Wang

{"title":"An one-dimensional signal based object detection network for apnea and hypopnea locating","authors":"Xian-Lung Tang, Liang Zhao, Yanping Shuai, Zhang Li, Xingjun Wang","doi":"10.1117/12.2643701","DOIUrl":"https://doi.org/10.1117/12.2643701","url":null,"abstract":"Sleep-disordered breathing (SDB), a common sleep disorder, shows symptoms of shallow breathing or paused breathing during sleep called respiratory events. SDB was conventionally diagnosed based on overnight multi-channel polysomnography (PSG) in clinical treatment. However, this process requires experienced sleep technicians to annotate and is quite labour-intensive. In this study, a novel one-dimensional signal based object detection network was proposed for automatic, high efficiency detection and classification of different kinds of respiratory events from continuous PSG signals. Our method can locate respiratory events in PSG signal data and classify them into four categories for further clinical treatment. The method was further validated on a PSG clinical dataset collected from Beijing Tongren Hospital. Precision, recall and F1-score of 84.9%, 85.1%, 85.0% were achieved for events detection with total accuracy rate reaching 74.9% in classification of detected events. The result shows that one-dimensional signal object detection is a promising method to locate the characteristic waveform and extract signal features. Such method can be applied in other signal feature detection field.","PeriodicalId":314555,"journal":{"name":"International Conference on Digital Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133536305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An evaluation method of aggregate morphological characteristics based on two-dimensional digital image technique 基于二维数字图像技术的聚集体形态特征评价方法

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2644604

Pei Sun, Zhenfeng Han

{"title":"An evaluation method of aggregate morphological characteristics based on two-dimensional digital image technique","authors":"Pei Sun, Zhenfeng Han","doi":"10.1117/12.2644604","DOIUrl":"https://doi.org/10.1117/12.2644604","url":null,"abstract":"Aggregate shape, angularity and surface texture are closely related to pavement performance of asphalt mixture. In order to quantitatively analyze the morphological characteristics of aggregates, the aggregate particle image was obtained by \"backlight scanning method\", and then noise removal, segmentation and hole filling are performed on the acquired image based on digital image processing technique. On the basis of above mentioned, a two-dimensional aggregate morphological characteristics evaluation system (AMCES) with low equipment requirements was developed. The shape property of aggregates were characterized by shape index (SI) and form factor (FF), and the angularity property and surface texture of aggregates were evaluated by angularity index (AI) and texture factor (TF) respectively. Finally, the morphological characteristics of 12 different standard shaped objects and limestone with 4 different sizes were analyzed. The test results show that the four evaluation parameters can describe the morphological characteristics of aggregate particles well. With the increase of particle size, the shape index decreases, the value of the form factor get closer and closer to 1, while the angularity index and texture factor both decrease gradually.","PeriodicalId":314555,"journal":{"name":"International Conference on Digital Image Processing","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129625689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An effective anti-interference visual tracking method 一种有效的抗干扰视觉跟踪方法

International Conference on Digital Image Processing Pub Date : 2022-10-12 DOI: 10.1117/12.2644230

Q. Fan, Yue Yang, E. Zou

引用次数: 0