Three-Stage Channel Split Dense Fusion Network for Single Image Deraining by ZHANG Shuting, WANG Changyue, WANG Changzhong, LENG Qiangkui

“…Single image deraining is a considerable challenge in the domain of image processing. …”
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Radar Coincidence Imaging for Off-Grid Target Using Frequency-Hopping Waveforms by Xiaoli Zhou, Hongqiang Wang, Yongqiang Cheng, Yuliang Qin, Haowen Chen

“…For off-grid RCI, the process is composed of two stages: grid matching and off-grid error (OGE) calibration, where two-dimension (2D) band-excluded locally optimized orthogonal matching pursuit (BLOOMP) and alternating iteration minimization (AIM) algorithms are proposed, respectively. …”
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Super-Resolution Imaging Through Scattering Medium Based on Parallel Compressed Sensing by Yao Zhao, Qian Chen, Shenghang Zhou, Guohua Gu, Xiubao Sui

“…However, traditional methods implemented measurement matrix by digital mirror device (DMD) or spatial light modulator, which is a serial imaging process and makes the method inefficient. …”
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Damage Scene Change Detection Based on Infrared Polarization Imaging and Fast-PCANet by Min Yang, Jie Yang, Hongxia Mao, Chong Zheng

“…Change detection based on optical image processing plays a crucial role in the field of damage assessment. …”
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A Variational Multi-Scale Error Compensation Network for Single-Pixel Imaging by Jian Lin, Qiurong Yan, Quan Zou, Shida Sun, Zhen Wei, Hua Du

“…However, conventional reconstruction algorithms suffer from issues such as long processing time and low reconstruction accuracy during the sampling and reconstruction processes. …”
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Progressive Conditional Diffusion Model for Multistage Spectral Restoration of Remote Sensing Image by Jinfeng Gao, Gangqiang Li, Ruxian Yao, Qiang Liu, Junming Zhang

“…However, most of these methods compute loss only at the final stage of the network, neglecting the intermediate generative processes, which leads to considerable spectral distortion in the reconstructed images. …”
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Corrosion Monitoring in Automotive Lap Joints Based on Imaging Methods of Lamb Waves by Yunmeng Ran, Cheng Qian, Xiangfen Wang, Weifang Zhang, Rongqiao Wang

“…To address this limitation, this study introduces a novel corrosion monitoring approach using Lamb wave-based weighted fusion imaging methods. First, the Minimum Variance Distortionless Response (MVDR) is utilized to process Lamb wave signals collected under bolt-loosening and bolt-tightening conditions to image the bolt locations. …”
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Menstrual cycle inspired latent diffusion model for image augmentation in energy production by Gamal M. Mahmoud, Mostafa Elbaz, Wael Said, Amira A. Elsonbaty

“…Latent diffusion models (LDMs) have shown potential in generating diverse images during the augmentation process based on text input. …”
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Multi-task feature integration and interactive active learning for scene image resizing by Ludan Shi, Xianhua Yan, Sen Wang

“…The primary advantages of LIAL are twofold: firstly, it maintains the local coherence of varied scenes efficiently, and secondly, it allows for the active selection process to be shaped by human interaction. By employing LIAL, we methodically represent a GSP for every scene and calculate its corresponding deep features by a multi-layer aggregating algorithm. …”
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A Composite Network for CS ISAR Integrating Deep Adaptive Sampling and Imaging by Lianzi Wang, Ling Wang, Miguel Heredia Conde, DaiYin Zhu

“…Compressive sensing (CS) actively contributes to inverse synthetic aperture radar (ISAR) imaging with less raw data. The design of the measurement matrix and the development of reconstruction methods are critical processes in CS ISAR imaging. …”
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Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques by Uwe Knauer, Sebastian Warnemünde, Patrick Menz, Bonito Thielert, Lauritz Klein, Katharina Holstein, Miriam Runne, Wolfgang Jarausch

“…Therefore, the potential of hyperspectral imaging in combination with data analysis by machine learning algorithms was investigated to detect the symptoms solely based on the spectral signature of collected leaf samples. …”
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Spatio-Spectral Structure Tensor Total Variation for Hyperspectral Image Denoising and Destriping by Shingo Takemoto, Kazuki Naganuma, Shunsuke Ono

“…This article proposes a novel regularization method, named <italic>spatio-spectral structure tensor total variation</italic> (<inline-formula><tex-math notation="LaTeX">${\text{S}_{3} \text{TTV}}$</tex-math></inline-formula>), for denoising and destriping hyperspectral (HS) images. HS images are inevitably contaminated by various types of noise during acquisition process due to the measurement equipment and the environment. …”
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A sustainable neuromorphic framework for disease diagnosis using digital medical imaging by Rutwik Gulakala, Marcus Stoffel

“…The models are trained using enhanced and pre-processed X-ray images and are evaluated based on classification metrics. …”
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Do more with less: Exploring semi-supervised learning for geological image classification by Hisham I. Mamode, Gary J. Hampson, Cédric M. John

“…But an alternative exists: there often is a large corpus of unlabeled data which may enhance the learning process. To evaluate this potential for subsurface data, we compare a high-performance semi-supervised learning (SSL) algorithm (SimCLRv2) with supervised transfer learning on a Convolutional Neural Network (CNN) in geological image classification.We tested the two approaches on a classification task of sediment disturbance from cores of International Ocean Drilling Program (IODP) Expeditions 383 and 385. …”
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RGB and RGNIR image dataset for machine learning in plastic waste detectionZENODO by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim, Nada Adam, Hadia Abdelgader Osman

“…The increasing volume of plastic waste is an environmental issue that demands effective sorting methods for different types of plastic. While spectral imaging offers a promising solution, it has several drawbacks, such as complexity, high cost, and limited spatial resolution. …”
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Segment search for local extremums of images based on the analysis of brightness of adjacent homogeneous areas by V. Yu. Tsviatkou, Anh Tuan Nguyen

“…The problem of finding local extrema on halftone images is considered. Well-known block-search algorithms provide high speed, but they extract only strict (single-pixel) extremes, skipping extreme areas formed by non-strict extremes. …”
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A System for the Real-Time Detection of the U-Shaped Steel Bar Straightness on a Production Line by Yen-Jen Chen, Yu-Hsiu Yeh, Jen-Fu Yang

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Magnetic Source Detection Using an Array of Planar Hall Effect Sensors and Machine Learning Algorithms by Miki Vizel, Roger Alimi, Daniel Lahav, Moty Schultz, Asaf Grosz, Lior Klein

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Region search based on hybrid convolutional neural network in optical remote sensing images by Shoulin Yin, Ye Zhang, Shahid Karim

“…This process avoids exhaustive search for input images. …”
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Classification of Toraja Wood Carving Motif Images Using Convolutional Neural Network (CNN) by Nurilmiyanti Wardhani, Billy Eden William Asrul, Antonius Riman Tampang, Sitti Zuhriyah, Abdul Latief Arda

“…This study not only underscores the effectiveness of processing in enhancing CNN capabilities but also opens opportunities for further research in applying these methods to various image types and exploring different CNN architectures.…”
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