Partitioning building groups at multiple scales based on image segmentation by Xianjin He, Puliang Lyu

“…First, image segmentation and merging approaches were employed to extract merged image regions, representing the spatial relationships of building groups. …”
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Study the noise effect on the edges and cross correlation of TV images by Abdullah .H. Muhammad, Layla Mahdi Salih

“…Because of that, it makes the interpretation and analysis of informative images   a very difficult process, and lessens their advantages. …”
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SGCM: Semantic and Geometric Consistency for Robust Aerial Image Matching by Xiangzeng Liu, Guanglu Shi, Chi Wang, Xiaodong Zhang, Qiguang Miao

“…Most current approaches primarily focus on low-level image features, while overlooking the potential of high-level semantic information to guide the matching process, limiting the robustness and accuracy of these methods in complex scenarios. …”
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Gray Extreme Weighted Sum Image Ringing Evaluation Algorithm by KE Ming, ZHANG Tian-ming, QIN Ai-jing, WANG Bo, BAI Xu

“…In the process of image blind restoration, the estimation of the fuzzy kernel usually produces errors which lead to image ringing The existing algorithm cannot effectively evaluate the severity of ringing To solve this problem, a method for evaluating the ringing effect is proposed From the physical mechanism of image ringing effect caused by blind restoration of image, the causes of the ringing effect caused by blind restoration of images and the influence on image quality are analyzed By extracting the overshoot and ripple regions of the ringing image and weighting the gradient values of the region, the severity of the ringing effect is quantified The experimental results show that when the fuzzy kernel parameter value exceeds 3, the algorithm shows a monotonically increasing state with increasing parameters,The change in SSIM evaluation results tends to be zero This algorithm can effectively evaluate different restoration algorithms and different restoration parameters Restore the ringing effect in the image under different restoration parameters…”
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Clouds Height Classification Using Texture Analysis of Meteosat Images by Baghdad Science Journal

“…The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. …”
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A Novel Printable Watermarking Method in Dithering Halftone Images by Hui-Lung Lee, Ling-Hwei Chen

“…In this paper, we will propose a novel printable watermarking method for dithering halftone images. Based on downsampling and the property of a dispersed dithering screen, the method can resist cropping, tampering, and print-and-scan process attacks. …”
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Deep-CNN for Disease Classification using Enhanced Mammographic Images by Ramesh Vaish, Praveen Kumar Shukla

“… Purpose: Breast cancer has become one of the most common diseases that women face today as a result of poor nutrition and other environmental factors. A mammogram image of the breast will help detect breast cancer, but still, sometimes doctors and radiologists are unable to detect it due to poor image quality or abnormal region that appears to be normal. …”
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Finite element analysis of mechanical impacts in large imaging detectors by Ma Li, Li Weibo, Zhang Hengwen, Wang Chunqiu

“…This study utilizes Ansys to analyze the stress distribution of a large imaging detector subjected to mechanical impacts, including vibration, shock loading, and collision, encountered during space missions. …”
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Multiple-Feature Construction for Image Segmentation Based on Genetic Programming by David Herrera-Sánchez, José-Antonio Fuentes-Tomás, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes, José-Luis Morales-Reyes

“…Within the medical field, computer vision has an important role in different tasks, such as health anomaly detection, diagnosis, treatment, and monitoring medical conditions. Image segmentation is one of the most used techniques for medical support to identify regions of interest in different organs. …”
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Reversible data hiding scheme based on enhanced image smoothness by Jinghan WANG, Hui ZHU, Helin LI, Hui LI, Xiaopeng YANG

“…With the prosperity of Internet technology and the popularity of social networks, reversible data hiding technology has been widely adopted in concealed information transmission of medical and military fields with its advantages on secret information recovery.Traditional reversible data hiding schemes mainly focus on the enhancement of embedding capacity and the reduction of the distortion rate of stego image, but pay less attention to the understanding of image details with the human eyes.Thus, it is difficult to resist hidden information detection methods.To solve the above challenge, a reversible data hiding algorithm was proposed, which ensured the visual quality of the stego image in the process of data hiding through the image visual smoothness enhancement.Specifically, the original image was divided into reference area and non-reference area.The secret data was embedded through the translation of the difference, which was calculated according to the predicted pixel value and the original pixel value of the non-reference area.To guarantee the visual quality of the image, smoothing mechanism was constructed, in which a Gaussian filter was utilized as a template to filter the predicted value and to add the filter difference into the cover image without loss.The pixel value of the reference region was used as edge information for lossless restoration of the original image.The filtering coefficient in Gaussian function was exploited as the embedded key to ensure the security of secret information.Simulation results regarding a large number of classical image data sets illustrated that the visual smoothness of stego image processed by this scheme was effectively enhanced with lower distortion rate, higher embedding rate, and higher embedding and extraction efficiency.In a typical circumstance, the similarity between the generated stego image and the Gaussian filter image can reach 0.9963.The PSNR and the embedded capacity can be up to 37.346 and 0.3289 BPP, respectively.…”
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Remote Sensing Image Interpretation for Coastal Zones: A Review by Shuting Sun, Qingqing Xue, Xinying Xing, Huihui Zhao, Fang Zhang

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Simplifying Masked Image Modeling With Symmetric Masking and Contrastive Learning by Khanh-Binh Nguyen, Chae Jung Park

“…Masked image modeling (MIM) has emerged as an effective self-supervised learning paradigm for pre-training Vision Transformers (ViTs) by reconstructing missing pixels from masked image regions. …”
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AITtrack: Attention-Based Image-Text Alignment for Visual Tracking by Basit Alawode, Sajid Javed

“…AITrack utilizes a region-of-interest (ROI) text-guided encoder that leverages existing pre-trained language models to implicitly extract and encode textual features and a simple image encoder to encode visual features. …”
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Lung Tumor Segmentation in Medical Imaging Using U-NET by J Jayapradha, Su-Cheng Haw, Naveen Palanichamy, Senthil Kumar Thillaigovindhan, Mutaz Al-Tarawneh

“…Images were cropped around the lower abdominal regions, and all images used in the study were then resized to 256*256 pixels for standardization. …”
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Adjoint-Assisted Shape Optimization of Microlenses for CMOS Image Sensors by Rishad Arfin, Jens Niegemann, Dylan McGuire, Mohamed H. Bakr

“…One of the fundamental factors determining the sensor’s ability to capture high-resolution images is its efficiency in focusing the visible light onto the photosensitive region of the submicron scale. …”
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Jet Archaeology and Forecasting: Image Variability and Magnetic Field Configuration by Yuh Tsunetoe, Ramesh Narayan, Angelo Ricarte

“…We also find in time-averaged images that both the bulk plasma motion and magnetic field configuration in the jet-launching region, which are sensitive to BH spin, shape diverse features through relativistic beaming and aberration. …”
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Towards edge-collaborative,lightweight and secure region proposal network by Jinbo XIONG, Renwan BI, Qianxin CHEN, Ximeng LIU

“…Aiming at the problem of image privacy leakage and computing efficiency in edge environment,a lightweight and secure region proposal network (SecRPN) was proposed.A series of secure computing protocols were designed based on the additive secret sharing scheme.Two non-collusive edge servers cooperate to perform calculation modules such as secure feature processing,secure anchor transformation,secure bounding-box correction,and secure non-maximum suppression.Theoretical analysis guarantees the correctness and security of SecRPN.The actual performance evaluation shows that SecRPN is outstanding in the computational cost and communication overhead compared with the existing works.…”
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Continuous theta-burst stimulation demonstrates language-network-specific causal effects on syntactic processing by Chenyang Gao, Junjie Wu, Yao Cheng, Yuming Ke, Xingfang Qu, Mingchuan Yang, Gesa Hartwigsen, Luyao Chen

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Spatio-temporal dynamics of sound-induced vestibular processing: insights from stereo-EEG recordings by Michele Terzaghi, Piergiorgio d'Orio, Ivana Sartori, Veronica Pelliccia, Flavia Maria Zauli, Silvia Colnaghi, Valter Rustioni, Fausto Caruana, Maria Del Vecchio, Maurizio Versino, Pietro Avanzini

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Efficient Generative-Adversarial U-Net for Multi-Organ Medical Image Segmentation by Haoran Wang, Gengshen Wu, Yi Liu

“…This mechanism enables the model to concentrate more effectively on regions of interest. Additionally, we have integrated Efficient Mapping Convolutional Blocks (EMCB) into the feature-learning process, allowing for the extraction of multi-scale spatial information and the adjustment of feature map channels through optimized weight values. …”
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