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2021 International conference on visual communications and image processing (VCIP) Proceedings

2021 International Conference on Visual Communications and I...

引用

IEEE visual communications and image processing (VCIP)

2021 International conference on visual communications and image processing (VCIP) Proceedings

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Computer graphics and image processing techniques based on visual communication design 4

Computer graphics and image processing techniques based on v...

引用

4th International conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Chen, Zhaoguo College of Arts Shandong Agricultural Engineering University Shandong Province Jinan250103 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

To fully harness the capabilities of computer graphics and image processing technologies and elevate the quality of visual communication design, this paper presents a comprehensive suite of innovative methodologies. Firstly, the fundamental principles of primary colors are utilized to formulate a series of vector functions, facilitating the precise calculation of error distances and the establishment of an intricate visual communication zoning model. Subsequently, through the exhaustive extraction of pertinent feature information from graphics and images, we achieve the scientific encoding of coefficient-constrained features and determine the corresponding hyperplanes to acquire the relevant parameters for visual communication. Eventually, the implementation of advanced design image expression algorithms markedly enhances the effectiveness of visual communication image representation. The empirical findings reveal that these visual communication design methods exhibit remarkable reliability and feasibility, effectively boosting image recognition accuracy across four distinct image categories with varying levels of complexity, thereby yielding exceptional visual communication outcomes. © 2025 SPIE.

关键词： Design visual communications visualization Computer graphics image processing image storage Color image segmentation image enhancement

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Hybrid Feature Approach for Enhancing Zero-Shot image Classification 4th

Hybrid Feature Approach for Enhancing Zero-Shot Image Classi...

引用

4th International conference on Artificial Intelligence and Knowledge processing

作者： Khanam, Shaista Sonar, Poonam N. Mumbai Univ Mumbai Maharashtra India

ISBN: (纸本)9783031734762;9783031734779

Zero-shot learning (ZSL) directs the challenge of classifying unseen test images without explicit training on those samples. ZSL can identify and classify unlabeled images available in abundance by learning from visual and semantic embedding vectors (feature vectors). Information-enriched visual features extracted from images play a crucial role in ZSL. This paper proposes a hybrid feature approach that integrates low-level (LL), and high-level (HL) features extracted from images. Gray Level Co-occurrence Matrix (GLCM) and Gabor features are employed to obtain LL texture features, while HL features are derived from the ResNet-50 model, renowned for capturing complex hierarchical representations. These hybrid visual features are then mapped with semantic features using linear mapping, where the semantic features are embedding vectors of labels generated by the fastText model. Experiments on the AWA2 and SUN datasets are conducted in a bid to evaluate the proposed approach's effectiveness. The hybrid feature approach has demonstrated enhanced quality in zero-shot image classification, effectively classifying images that the model has not seen during training.

关键词： Hybrid feature Zero-shot image classification GLCM

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image Generation from Arabic Text: Comparative Study of Proposed Architectures 8th

Image Generation from Arabic Text: Comparative Study of Prop...

引用

8th International conference on Arabic Language processing

作者： Bahani, Mourad El Ouaazizi, Aziza Maalmi, Khalil Essahlaoui, Abdelouahed Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Artificial Intelligence Data Sci & Emerging Syst Fes Morocco Sidi Mohamed Ben Abdellah Univ Lab Engn Sci FPT Taza Morocco

ISBN: (纸本)9783031804373;9783031804380

Text-to-image generation is a cutting-edge technology that enables computers to generate images from textual descriptions. While this technology has been extensively researched and applied to English language text, applying it to Arabic language text is still in its early stages. Additionally, the Arabic language is challenging due to its right-to-left writing system and extensive vocabulary of 1.3 million words. In this paper, we explore text-to-image generation for generating images from Arabic language text descriptions. Firstly, we fine-tune a transformer-based model pre-trained on the Arabic text to transform the text information into affine transformation within the DF-GAN generator. Secondly, we present a text transformer that combines LSTM layers to address the limitation of unrecognized words. Thirdly, a mask predictor is trained into the generator using a weakly supervised method and incorporated into the affine transformation for a more effective integration of image and text features. In addition, we add the DAMSM loss function as a regularization to the loss function to achieve convergences and stability in the training phase. The experiment on two challenging datasets CUB and Oxford-flower shows that our architectures can accurately generate high-quality images faithfully representing the Arabic textual descriptions. We believe the scaling of this task could have critical applications in fields such as Arabic visual learning, e-commerce, advertising, and entertainment.

关键词： Machine Learning Deep Learning Computer Vision Generative Adversarial Networks Text-to-image Generation Arabic Text processing

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Design and Implementation of image Description Model Using Artificial Intelligence Based Techniques 3rd

Design and Implementation of Image Description Model Using A...

引用

3rd International conference on Computational Electronics for Wireless communications, ICCWC 2023

作者： Ingale, Sumedh Bamnote, G.R. Prof. Ram Meghe Institute of Technology & Research Badnera Amravati India

ISBN: (纸本)9789819719457

The process that produces written descriptions that effectively represent the meaning and context of an image is known as image captioning. To integrate visual and textual data, it needs to blend computer vision and natural language processing methods. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs), such as long-short-term memory (LSTM) networks, are two methods used for captioning images. High-level visual features from the input image are extracted by the CNN, and the RNN uses those features to generate the matching captions. Residual Network is a deep CNN architecture with exceptional results in a range of computer vision tasks, including the classification of images. ResNet has been used as the foundation for extracting picture features. ResNet and CNN abstracts an image's visual information via feature extraction and uses neural networks with recurrent architecture to provide meaningful, contextually appropriate captions. Machines are now able to comprehend and speak about the visual world in a manner similar to humans because of the integration of computer vision and natural language processing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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image Captioning with Multiple Perspectives—A visual Context-Based Approach 5th

Image Captioning with Multiple Perspectives—A Visual Contex...

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5th International conference on Computing and Network communications, CoCoNet 2023

作者： Ashwin, G. Chaitanya, V. Kishan Rohith Nair, Priyanka C. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru560035 India

ISBN: (纸本)9789819747108

This study tackles the difficult issues of image captioning while negotiating the complexity of visual data processing. The complexity of visual data and the associated processing requirements make image captioning a daunting task. This research describes an effective method for image captioning that makes advantage of attentional mechanisms. Several models, including Transformer, VGG16, VGG19, Inception, RNN decoders, and Bahdanau’s attention mechanism, are contrasted and analyzed to demonstrate the benefits of integrating attention processes. By allowing the model to focus on the appropriate visual component, attention improves the accuracy of the generated captions. Transformer models, in particular, outperform other methods by capturing complicated relationships and delivering accurate output, and they have the highest BLEU Score of 70. The findings emphasize the significance of attention mechanisms and the relevance of selecting a suitable model architecture to maximize picture captioning performance. The variety of potential applications emphasizes the benefits and potential impact of image captioning in a broad range of scenarios. Several use cases are found beneficial, including supporting the visually impaired, improving product descriptions in e-commerce, assisting medical diagnosis, improving image search ability, and allowing effective communication and comprehension of visual information. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Diagnosis

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6th International image processing and communications conference, IPandC 2014

6th International Image Processing and Communications Confer...

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6th International image processing and communications conference, IPandC 2014

ISBN: (纸本)9783319106618

The proceedings contain 39 papers. The special focus in this conference is on image processing and communications. The topics include: Two-Dimensional hidden Markov models in road signs recognition;evaluating the mutual position of objects on the visual scene using morphological processing and reasoning;clustering-based retrieval of similar outfits based on clothes visual characteristics;improving shape retrieval and classification rates through low-dimensional features fusion;accelerating the 3D random walker image segmentation algorithm by image graph reduction and GPU computing;computed tomography images denoising with Markov random field model parametrized by Prewitt mask;Gaussian mixture model based non-local means technique for mixed noise suppression in color images;robust image retrieval based on mixture modeling of weighted Spatio-color information;noise reduction in ultrasound images based on the concept of local neighbourhood exploration;Viterbi algorithm for noise line following robots;hybrid shape descriptors for an improved weld defect retrieval in radiographic testing;on the usefulness of combined metrics for 3D image quality assessment;image processing with process migration;comparison of assessment regularity methods dedicated to isotropic cells structures analysis;a texture-based energy for active contour image segmentation;object localization and detection using variance filter;the impact of the image feature detector and descriptor choice on visual SLAM accuracy and shape versus texture.

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Proceedings EC-VIP-MC 2003 - 4th EURASIP conference Focused on Video / image processing and Multimedia communications

Proceedings EC-VIP-MC 2003 - 4th EURASIP Conference Focused ...

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4th EURASIP conference Focused on Video / image processing and Multimedia communications, EC-VIP-MC 2003

ISBN: (纸本)9531840547

The proceedings contain 131 papers. The topics discussed include: multimedia in Croatian digital video broadcasting;signal and image data processing in ultrasonic imaging;progressive image coding using regional color correlation;edge-preserving regularization of disparity and motion fields;an edge-preserving high-resolution image reconstruction;a new method for image coding in computer vision;efficient post-processing for block-based compressed video;detecting lesions in a mammogram;a methodology for evaluating the operational effectiveness of facial recognition systems;gallery image effects on facial recognition systems;on edge detection in MRI using the wavelet transform and unsupervised neural networks;improved illumination independent moving object detection in real world video sequences;and virtual image : keyframe or visual icon?.

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Proceedings EC-VIP-MC 2003 - 4th EURASIP conference Focused on Video / image processing and Multimedia communications

Proceedings EC-VIP-MC 2003 - 4th EURASIP Conference Focused ...

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4th EURASIP conference Focused on Video / image processing and Multimedia communications, EC-VIP-MC 2003

ISBN: (纸本)9531840547

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Joint Dehazing and Low-light image Enhancement with Complete Atmospheric Model 16

Joint Dehazing and Low-light Image Enhancement with Complete...

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16th International conference on Signal processing Systems, ICSPS 2024

作者： Wu, Yong Xia, Kexiang Ge, Liyong Ye, Jiongkai Zhejiang Institute of Communications Hangzhou311112 China The School of Automation Hangzhou Dianzi University Hangzhou310000 China

ISBN: (纸本)9781510689251

Current image dehazing algorithms often encounter issues of contrast reduction and color distortion in the shadow regions of images. To address this challenge, this paper proposes a comprehensive atmospheric model that simultaneously considers haze and low-light conditions. This model incorporates a global darkness factor as a disturbance variable alongside the atmospheric scattering model, enabling adaptive luminance balancing without the need to estimate the global atmospheric light or the global darkness factor. Building on the principle of object color rendition, This paper justifies the use of the dark channel prior for haze removal and extends the bright channel prior for low-light image enhancement. Furthermore, we explore the mapping relationship between normal and inverted images based on the complete atmospheric model. By solving for the transmission rates of the global atmospheric light and global darkness factor, we propose an image enhancement algorithm capable of concurrently processing haze and low-light images. The proposed algorithm effectively mitigates issues of contrast reduction and color distortion. Experimental results demonstrate the efficacy of our approach, showing that the visual outcomes of simultaneous haze removal and low-light enhancement surpass those achieved through single-task haze removal. © 2025 SPIE.

关键词： Demulsification

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