The proceedings contain 12 papers. The special focus in this conference is on Computational Mathematics Modeling in Cancer analysis. The topics include: Follicular Lymphoma Grading Based on 3D-DDcGAN and Bay...
ISBN:
(纸本)9783031733598
The proceedings contain 12 papers. The special focus in this conference is on Computational Mathematics Modeling in Cancer analysis. The topics include: Follicular Lymphoma Grading Based on 3D-DDcGAN and Bayesian CNN Using PET-CT images;Multi-channel Multi-model Fusion Module (MMFM) Based Circulating Abnormal Cells (CACs) Detection for Lung Cancer Early Diagnosis with Fluorescence in Situ Hybridization (FISH) images;domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation;Attention-Fusion Model for Multi-omics (AMMO) Data Integration in Lung Adenocarcinoma;PD-L1 Expression Prediction Using Scalable Multi Instance Transformer;improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation;PANDA: Pneumonitis Anomaly Detection Using Attention U-Net;estimating the Average Treatment Effect Using Weighting Methods in Lung Cancer Immunotherapy;Beyond Conventional Parametric Modeling: Data-Driven Framework for Estimation and Prediction of Time Activity Curves in Dynamic PET Imaging;assessment of Radiomics Feature Repeatability and Reproducibility and Their Generalizability Across image Modalities by Perturbation in Nasopharyngeal Carcinoma Patients.
In machine/computer vision, cameras serve a major role in image acquisition. Surveillance scenarios typically rely on Closed-Circuit Television (CCTV) cameras. This study aims to evaluate industrial cameras within a s...
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ISBN:
(纸本)9798350350494;9798350350500
In machine/computer vision, cameras serve a major role in image acquisition. Surveillance scenarios typically rely on Closed-Circuit Television (CCTV) cameras. This study aims to evaluate industrial cameras within a surveillance application, contrasting their performance with that of CCTV cameras. We explore the comparative analysis of CCTV and industrial cameras for vehicle attribute recognition, specifically concentrating on the recognition of vehicle color and model using deep learning techniques. To train and evaluate the models, we have created datasets from images captured by both a CCTV and an industrial camera. Our findings indicate that the industrial camera outperforms the CCTV. However, employing advanced processing algorithms has the potential to minimize the performance gap between these two cameras. Our research represents one of the initial comparative analyses between these camera types, offering valuable guidance in selecting the most suitable camera for specific applications.
This paper presents a novel approach to license plate recognition in Iran's transportation system by employing a fuzzy-based algorithm. The proposed method involves a four-stage process, including the conversion o...
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ISBN:
(纸本)9798350350494;9798350350500
This paper presents a novel approach to license plate recognition in Iran's transportation system by employing a fuzzy-based algorithm. The proposed method involves a four-stage process, including the conversion of RGB images to grayscale, fuzzy thresholding using a Fuzzy Inference System (FIS), character segmentation, and application of fuzzy clustering for license plate number detection. Simulation results demonstrate the effectiveness of the proposed method in achieving rapid and accurate license plate number detection.
Generative Adversarial Network (GAN) is a powerful generative model based on deep learning. At present, it is widely used in computer vision, natural language processing, semi-supervised learning and other fields, and...
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ISBN:
(纸本)9798400716959
Generative Adversarial Network (GAN) is a powerful generative model based on deep learning. At present, it is widely used in computer vision, natural language processing, semi-supervised learning and other fields, and has achieved remarkable results. This paper adopts the bibliometric analysis method, and uses InCites and VOSviewer tools to quantitatively study and visualize the papers of generative adversarial networks. Through the analysis and comparison of countries, institutions, and researchers, a comprehensive portrait of the academic achievements in the field of GAN is portrayed: GAN research reached a peak in 2021;Deep learning, Super-Resolution, Face recognition, image Enhancement, Speech recognition, Object Tracking, Intrusion Detection are hotspots;China and the United States have published the most papers;Chinese institutions lack both international and corporate cooperation, and Chinese researchers need more innovative research on theories.
With the rapid development of digital media technology, imageanalysis plays a vital role in the fields of digitalization and informatization. This article will provide an in-depth explanation of face recognition and ...
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With the rapid development of deep learning technology, its application in image processing and recognition has become a hot research topic. The application of these technologies in software information systems such a...
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This paper presents a simple approach leveraging temporal learning on informative frames for action recognition. We propose a training-free simple adaptive frame selection scenario employing just the similarity techni...
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ISBN:
(纸本)9798350350494;9798350350500
This paper presents a simple approach leveraging temporal learning on informative frames for action recognition. We propose a training-free simple adaptive frame selection scenario employing just the similarity technique in a temporal window. The proposed frame selection method provides an appropriate strategy to capture informative frames and provide meaningful features. Moreover, we use transfer learning for spatial feature extraction and employ LSTM and GRU for temporal modeling. Our method is evaluated on two popular datasets, UCF11 and KTH, and it demonstrates acceptable results.
This study aims to explore the grotto color analysis based on image processing and its application in environmental design. By using multispectral and hyperspectral imaging techniques, we collected and analyzed the co...
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This study addresses the crucial task of architectural decorative image pattern recognition in the context of iconography, with an emphasis on efficient information mining. The proposed research work presents a novel ...
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In this paper, an image-based gesture recognition system has been presented for finger hand rehabilitation using a low-cost camera. Since the goal is to set up a low-cost home rehabilitation system, the analysis of ea...
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ISBN:
(纸本)9798350350494;9798350350500
In this paper, an image-based gesture recognition system has been presented for finger hand rehabilitation using a low-cost camera. Since the goal is to set up a low-cost home rehabilitation system, the analysis of each finger should be easily possible for the user, and the user should be able to follow the information of the improvement process of one's treatment. Hence, first, the models governing the movement angles of the fingers were established, and then some criteria have been developed to evaluate the improvement of the performance of the fingers. Finally, several deep-learning models were initially implemented to extract the hand gesture and model parameters and based on the experimental results, the MediaPipe framework was found suitable due to its precision and robustness to determine the finger angles in low quality images during each exercise.
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