標(biāo)題: Titlebook: Computer Vision and Image Processing; 8th International Co Harkeerat Kaur,Vinit Jakhetiya,Sanjeev Kumar Conference proceedings 2024 The Edi [打印本頁] 作者: BOUT 時(shí)間: 2025-3-21 16:05
書目名稱Computer Vision and Image Processing影響因子(影響力)
書目名稱Computer Vision and Image Processing影響因子(影響力)學(xué)科排名
書目名稱Computer Vision and Image Processing網(wǎng)絡(luò)公開度
書目名稱Computer Vision and Image Processing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computer Vision and Image Processing被引頻次
書目名稱Computer Vision and Image Processing被引頻次學(xué)科排名
書目名稱Computer Vision and Image Processing年度引用
書目名稱Computer Vision and Image Processing年度引用學(xué)科排名
書目名稱Computer Vision and Image Processing讀者反饋
書目名稱Computer Vision and Image Processing讀者反饋學(xué)科排名
作者: Hemoptysis 時(shí)間: 2025-3-21 23:58
Automated Detection of Cracks in Asphalt Pavement Images Using Texture Descriptors and Machine Learck. The manual approaches for evaluating a pavement is done by the experts which consumes more time and the occasionally produces subjective results. Hence an 2D digital road image is analyzed to detect the crack automatically. The proposed work focuses on the pre-processing the image, extracting th作者: Morbid 時(shí)間: 2025-3-22 00:55 作者: Hirsutism 時(shí)間: 2025-3-22 07:59 作者: Lipoma 時(shí)間: 2025-3-22 12:31
,On the?Application of?Log Compression and?Enhanced Denoising in?Contrast Enhancement of?Digital Radbased on as low as reasonably achievable (ALARA) principle is employed and this results in low contrast images. To address this issue, post-processing algorithms such as the Multiscale Image Contrast Amplification (MUSICA) algorithm can be used to enhance the contrast of DR images even with a low ra作者: mercenary 時(shí)間: 2025-3-22 14:29
,A Lightweight UNet with?Inverted Residual Blocks for?Diabetic Retinopathy Lesion Segmentation,d by subtle variations among different grades and the presence of numerous important small features, poses a considerable challenge for accurate recognition. Currently, the process of identifying DR relies heavily on the expertise of physicians, making it a time-consuming and labor-intensive task. H作者: mercenary 時(shí)間: 2025-3-22 19:28
,A Belief Theory Based Instance Selection Scheme for?Label Noise and?Outlier Detection from?Breast Cgorithms including support vector machine (SVM) is sensitive to noise and outlier samples which can degrade their performance. Belief theory which involves an extension of the general probabilistic model and utilises combination rules for information fusion has found good use in the realm of classif作者: Nuance 時(shí)間: 2025-3-23 01:13 作者: 平淡而無味 時(shí)間: 2025-3-23 03:30 作者: 中和 時(shí)間: 2025-3-23 08:35
Uncovering the Extent of Flood Damage using Sentinel-1 SAR Imagery: A Case Study of the July 2020 Fn July 2020 were mainly due to the heavy monsoon rainfall in the region. The Brahmaputra River and its tributaries, which pass through the state, received substantial rainfall, leading to a sudden increase in water levels and flooding in multiple districts. The state‘s topography, hills, and valleys作者: Adulate 時(shí)間: 2025-3-23 13:45
,Robust Unsupervised Geo-Spatial Change Detection Algorithm for?SAR Images, unsupervised grid graph generation algorithm specifically designed for change detection using Synthetic Aperture Radar (SAR) images. The proposed technique encompasses a multi-step process: starting with an improved log-ratio based difference image generation, followed by shortest path vector compu作者: intellect 時(shí)間: 2025-3-23 16:33 作者: 虛構(gòu)的東西 時(shí)間: 2025-3-23 21:12 作者: graphy 時(shí)間: 2025-3-24 01:23 作者: Creatinine-Test 時(shí)間: 2025-3-24 04:02 作者: 減去 時(shí)間: 2025-3-24 08:37 作者: 云狀 時(shí)間: 2025-3-24 11:17
MuSTAT: Face Ageing Using Multi-scale Target Age Style Transfer,age gap. Although this can be solved using data collected over long age spans, it is challenging and tedious. This work proposes a multi-scale target age-based style face ageing model using an encoder-decoder architecture to generate high-fidelity face images under ageing. Further, we propose using 作者: Encephalitis 時(shí)間: 2025-3-24 15:09
,Efficient Contextual Feature Network for?Single Image Super Resolution,g feature utilization through complex layer connections. However, these methods may not be suitable for resource-constrained devices due to their computational demands. We propose a novel approach called Efficient Contextual Feature Network (ECFN) to address this issue. ECFN utilizes two convolution作者: Opponent 時(shí)間: 2025-3-24 20:22
T-Fusion Net: A Novel Deep Neural Network Augmented with Multiple Localizations Based Spatial Attenworks. Nonetheless, the growing complexity of datasets and the ongoing pursuit of enhanced performance necessitate innovative approaches. In this study, we introduce a novel deep neural network, referred to as the “T-Fusion Net,” which incorporates multiple spatial attention mechanisms based on loca作者: GEST 時(shí)間: 2025-3-24 23:51 作者: coalition 時(shí)間: 2025-3-25 05:54 作者: 替代品 時(shí)間: 2025-3-25 10:29 作者: 策略 時(shí)間: 2025-3-25 13:04
,Robust Unsupervised Geo-Spatial Change Detection Algorithm for?SAR Images,ge data and is benchmarked against state-of-the-art methods. Results demonstrate the resilience and superior performance of the proposed method in comparison to existing approaches in terms of robustness and speed.作者: insipid 時(shí)間: 2025-3-25 19:08 作者: Archipelago 時(shí)間: 2025-3-25 22:08
1865-0929 eedings were carefully reviewed and selected from?461?submissions.?The papers focus on?various important and emerging topics in image processing, computer vision applications, deep learning, and machine learning techniques in the domain..978-3-031-58173-1978-3-031-58174-8Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: Glaci冰 時(shí)間: 2025-3-26 00:41 作者: Ingratiate 時(shí)間: 2025-3-26 06:31
https://doi.org/10.1007/978-94-017-0703-9curacy. In this work, we have modified a transformer-based architecture called Segformer for semantic segmentation of 3D sliced data. Our method leverages transfer learning on low-population data. With a new advanced masking logic, we achieve 99% accuracy for segmentation and labeling of lumbar spine MR images.作者: Obsessed 時(shí)間: 2025-3-26 10:59 作者: Instrumental 時(shí)間: 2025-3-26 14:55 作者: Supplement 時(shí)間: 2025-3-26 19:03 作者: Fermentation 時(shí)間: 2025-3-27 00:21 作者: ligature 時(shí)間: 2025-3-27 03:51
,Efficient Contextual Feature Network for?Single Image Super Resolution,al layers to learn residual contextual local features, striking a balance between model effectiveness, inference speed, and efficiency. These updates improve performance compared to previously reported efficient super-resolution models for Single Image Super-Resolution (SISR), offering faster runtime without compromising high PSNR or SSIM.作者: LAITY 時(shí)間: 2025-3-27 08:50
1865-0929 omputer Vision and Image Processing, CVIP 2023, held in Jammu, India, during November 3–5, 2023.?..The 140 revised full papers presented in these proceedings were carefully reviewed and selected from?461?submissions.?The papers focus on?various important and emerging topics in image processing, comp作者: fiscal 時(shí)間: 2025-3-27 10:29
Emmanuel Godard,Dorian Mazauricically for DR images. The conclusion is that combining log compression and its inverse at the appropriate stage with a multi-stage MUSICA and denoising is very promising. The proposed method resulted in an average of 66.5% increase in the mean contrast-to-noise ratio (CNR) for the test images considered.作者: forestry 時(shí)間: 2025-3-27 16:10
,On the?Application of?Log Compression and?Enhanced Denoising in?Contrast Enhancement of?Digital Radically for DR images. The conclusion is that combining log compression and its inverse at the appropriate stage with a multi-stage MUSICA and denoising is very promising. The proposed method resulted in an average of 66.5% increase in the mean contrast-to-noise ratio (CNR) for the test images considered.作者: 壁畫 時(shí)間: 2025-3-27 19:34
https://doi.org/10.1007/978-1-4612-0323-0uch as Gaussian and shot noise appear on images due to digital fluctuations. Unfortunately, standard vision models tend to perform quite poorly under such unavoidable corruptions, ., these models are not robust to the distribution shifts induced by these corruptions at test time. The standard approa作者: 陶瓷 時(shí)間: 2025-3-28 00:47
Algorithms for Reinforcement Learningck. The manual approaches for evaluating a pavement is done by the experts which consumes more time and the occasionally produces subjective results. Hence an 2D digital road image is analyzed to detect the crack automatically. The proposed work focuses on the pre-processing the image, extracting th作者: MARS 時(shí)間: 2025-3-28 02:29 作者: 冰河期 時(shí)間: 2025-3-28 07:40 作者: 思想流動(dòng) 時(shí)間: 2025-3-28 12:21 作者: 絆住 時(shí)間: 2025-3-28 18:16
Abdullah Almethen,Othon Michail,Igor Potapovd by subtle variations among different grades and the presence of numerous important small features, poses a considerable challenge for accurate recognition. Currently, the process of identifying DR relies heavily on the expertise of physicians, making it a time-consuming and labor-intensive task. H作者: Alienated 時(shí)間: 2025-3-28 21:51 作者: 龍卷風(fēng) 時(shí)間: 2025-3-29 00:52
Iman Bagheri,Lata Narayanan,Jaroslav Opatrnyfaces challenges due to altitude, motion blur, and limited resolution. Early detection and identification of these diseases can help prevent their spread and minimize the impact on crop yields. To address the challenge of capturing high-quality images, this paper relies on the new degradation model 作者: Eclampsia 時(shí)間: 2025-3-29 05:43
https://doi.org/10.1007/978-3-030-34405-4ortant role as it can affect the efficiency of the learning algorithm and also reduce the redundancy. In this article, a different look on the problem has been explored where application of biogeography based optimization is used for efficient dimensionality reduction in hyperspectral images. After 作者: 愛好 時(shí)間: 2025-3-29 11:10
https://doi.org/10.1007/978-3-540-74991-2n July 2020 were mainly due to the heavy monsoon rainfall in the region. The Brahmaputra River and its tributaries, which pass through the state, received substantial rainfall, leading to a sudden increase in water levels and flooding in multiple districts. The state‘s topography, hills, and valleys作者: 反復(fù)無常 時(shí)間: 2025-3-29 11:58
https://doi.org/10.1007/978-3-030-96166-4 unsupervised grid graph generation algorithm specifically designed for change detection using Synthetic Aperture Radar (SAR) images. The proposed technique encompasses a multi-step process: starting with an improved log-ratio based difference image generation, followed by shortest path vector compu作者: interior 時(shí)間: 2025-3-29 18:02 作者: HAWK 時(shí)間: 2025-3-29 20:09 作者: Orchiectomy 時(shí)間: 2025-3-30 01:33 作者: 尾隨 時(shí)間: 2025-3-30 04:44
https://doi.org/10.1007/978-94-017-0703-9 structure of a spine accurately, hence it is essential to demarcate and identify the vertebra in the MRI image. There are both supervised and unsupervised methods for vertebra segmentation and labeling. However, the acquisition of requisite data is a challenge to designing methods with very high ac作者: Iatrogenic 時(shí)間: 2025-3-30 10:45
Jan Korst,Joep van Gassel,Ruud Wijnandsproblem, where an image is given as input and intensity value is estimated as output. In the literature, various deep learning methods have been proposed for TC intensity estimation but their focus on cyclones around the Indian subcontinent is limited. We have implemented three models: regression mo作者: 地名詞典 時(shí)間: 2025-3-30 14:57
https://doi.org/10.1007/978-3-642-61568-9age gap. Although this can be solved using data collected over long age spans, it is challenging and tedious. This work proposes a multi-scale target age-based style face ageing model using an encoder-decoder architecture to generate high-fidelity face images under ageing. Further, we propose using 作者: 銀版照相 時(shí)間: 2025-3-30 18:00 作者: Narcissist 時(shí)間: 2025-3-31 00:03
https://doi.org/10.1007/978-3-642-61568-9works. Nonetheless, the growing complexity of datasets and the ongoing pursuit of enhanced performance necessitate innovative approaches. In this study, we introduce a novel deep neural network, referred to as the “T-Fusion Net,” which incorporates multiple spatial attention mechanisms based on loca作者: pulmonary 時(shí)間: 2025-3-31 03:50
Computer Vision and Image Processing978-3-031-58174-8Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: BET 時(shí)間: 2025-3-31 08:23 作者: 陰險(xiǎn) 時(shí)間: 2025-3-31 09:51
978-3-031-58173-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 卷發(fā) 時(shí)間: 2025-3-31 15:21
Communications in Computer and Information Sciencehttp://image.papertrans.cn/d/image/242299.jpg作者: febrile 時(shí)間: 2025-3-31 19:23
https://doi.org/10.1007/978-1-4612-0323-0intain robustness to few high-frequency corruptions at high severity levels. Analyzing the Fourier signature of those corruptions reveal a change in behavior - at high severity they corrupt low frequencies as well. A Gaussian-trained model loses its performance due to this change. Current augmentati作者: Aspirin 時(shí)間: 2025-4-1 01:00
Algorithms for Reinforcement Learningntation was performed on the four standard dataset like Road Damage Dataset (RDD)-2018, Road Damage Dataset (RDD)-2019, Road Damage Dataset (RDD)-2020 and Road Damage Dataset (RDD)-2022 considering the different locations and uneven illumination condition. From the study it is figured out that Co-oc作者: 設(shè)施 時(shí)間: 2025-4-1 03:43
The Multi-source Beachcombers’ Problemed robust results, while Inception-V3 lagged behind. The findings demonstrate the effectiveness of deep learning architectures in the automatic assessment of bowel cleanliness in colonoscopy procedures.作者: set598 時(shí)間: 2025-4-1 08:35
Abdullah Almethen,Othon Michail,Igor Potapov leading to ambiguous results. In this work, a shallow UNet-based architecture with inverted residual skip connections is proposed to segment lesion parts of DR disease. Performance of the model is evaluated on Indian Diabetic Retinopathy Image Dataset (IDRiD) and DDR datasets. Results show that the作者: 流動(dòng)才波動(dòng) 時(shí)間: 2025-4-1 12:15
Collaborative Broadcast in , Roundsevaluation is done by considering accuracy and confusion matrix measures. Effect of noise is assessed by testing on the datasets after contaminating the training data by random mislabelling. Results are compared with the conventional SVM algorithm for both the noisy and noiseless datasets. The propo作者: 灌輸 時(shí)間: 2025-4-1 15:05
Iman Bagheri,Lata Narayanan,Jaroslav Opatrnyset with dimensions of .. Subsequently, the dataset is labeled using the publicly available tool makesense.ai (makesense.ai: .), based on three categories of crop health: (a) Healthy, (b) Potato Leafroll Virus (PLRV), and (c) Verticillium wilt, as specified by the Potato Disease Identification, Agri作者: arthroplasty 時(shí)間: 2025-4-1 21:32 作者: 樹木心 時(shí)間: 2025-4-2 02:05
Dereje W. Gudicha,Jeroen K. VermuntUsing the MobileNet model, the federated and centralized frameworks have achieved an accuracy of 95% and 92%, respectively. These findings encourage clinicians around the globe to utilize wealthy private data without violating privacy laws using federated learning to build a powerful model for class作者: 召集 時(shí)間: 2025-4-2 03:52
https://doi.org/10.1007/978-3-319-00035-0named Fusion-based Residual Transformer (FRESFORMER) architecture. Our proposed model tops the performance on the benchmark ISBI 2019 challenge dataset. The proposed model achieves an F1-Score of 84.89.
