Next-Gen Video Watermarking with Augmented Payload: Integrating KAZE and DWT for Superior Robustness and High Transparency by Himanshu Agarwal, Shweta Agarwal, Farooq Husain, Rajeev Kumar

“…Utilizing the 2D-DWT along with the KAZE feature detection algorithm, which incorporates the Accelerated Segment Test with Zero Eigenvalue, scrutinize and pinpoint data points that exhibit circular symmetry. …”
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Increasing the Classification Achievement of Steel Surface Defects by Applying a Specific Deep Strategy and a New Image Processing Approach by Fatih Demir, Koray Sener Parlak

“…Defect detection is still challenging to apply in reality because the goal of the entire classification assignment is to identify the exact type and location of every problem in an image. …”
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Research and Experiment on a Chickweed Identification Model Based on Improved YOLOv5s by Hong Yu, Jie Zhao, Xiaobo Xi, Yongbo Li, Ying Zhao

“…Currently, multi-layer deep convolutional networks are mostly used for field weed recognition to extract and identify target features. However, in practical application scenarios, they still face challenges such as insufficient recognition accuracy, a large number of model parameters, and slow detection speed. …”
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Underground personnel recognition based on low-light enhancement of infrared and visible light image fusion by NAN Jingjing, PAN Hongguang, JIANG Ze, ZHANG Libin, ZHANG Huipeng

“…Compared to the infrared modality, accuracy increased by an average of 2.1%, recall rate increased by 5.1%, and mAP@0.5 increased by 4.1%. Meanwhile, the detection speed reached 31.2 frames/s, solving problems such as misdetection and missed detection caused by unclear personnel features in low-light underground scenarios.…”
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A Novel LSTM Architecture for Automatic Modulation Recognition: Comparative Analysis With Conventional Machine Learning and RNN-Based Approaches by Sam Ansari, Soliman Mahmoud, Sohaib Majzoub, Eqab Almajali, Anwar Jarndal, Talal Bonny

“…The recognition of modulation types in received signals is essential for signal detection and demodulation, with broad applications in telecommunications, defense, and wireless communications. …”
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An Effective Strategy of Object Instance Segmentation in Sonar Images by Pengfei Shi, Huanru Sun, Qi He, Hanren Wang, Xinnan Fan, Yuanxue Xin

“…By integrating this with ResNet and transforming traditional convolutions into deformable convolutions, we further improve the ability of the network to extract features from sonar images. Additionally, we incorporate a bidirectional feature fusion module to enhance information fusion. …”
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Attention-Based Lightweight YOLOv8 Underwater Target Recognition Algorithm by Shun Cheng, Zhiqian Wang, Shaojin Liu, Yan Han, Pengtao Sun, Jianrong Li

“…It solves the problems of high computational complexities, slow detection speeds and low accuracies. …”
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Identification of line status changes using phasor measurements through deep learning networks by N. E. Gotman, G. P. Shumilova

“…THE PURPOSE. To consider the problem of detecting changes in a power grid topology that occurs as a result of the power line outage / turning on. …”
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Multispectral image fusion method based on edge chromatic aberration by Y. Shi, D. Qiu, R. Wu, R. Wu, W. Niu, Z. Wang

“…This method effectively solves the problems of multi-scale feature extraction and texture distortion of cracks through adaptive color difference correction and spectral consistency constraints, providing high-precision data support for intelligent road maintenance.…”
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Opposition-Based White Shark Optimizer for Optimizing Modified EfficientNetV2 in Road Crack Classification by Mohammed Al-Shalabi, Mohammed A. Mahdi, Malik Braik, Mohammed Azmi Al-Betar, Shahanawaj Ahamad, Sawsan A. Saad

“…The outcome emphasizes its ability to identify the most effective solution for crack detection in practical scenarios, where PCA-based feature selection improves computational efficiency without compromising performance. …”
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Crop-Free-Ridge Navigation Line Recognition Based on the Lightweight Structure Improvement of YOLOv8 by Runyi Lv, Jianping Hu, Tengfei Zhang, Xinxin Chen, Wei Liu

“…The results indicate that the model maintains high accuracy while significantly outperforming Mask-RCNN, YOLACT++, YOLOv8, and YOLO11 in terms of computational speed. The detection frame rate increased significantly, improving the real-time performance of detection. …”
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An appraisal of backscatter removal and refraction calibration models for improving the performance of vision-based mapping and navigation in shallow underwater environments by Fickrie Muhammad, Poerbandono, Harald Sternberg, Eka Djunarsjah, Hasanuddin Z Abidin

“…The research shows efficient backscatter removal improves feature detection robustness, especially in murky water conditions. …”
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Analog Circuits Fault Diagnosis Using ISM Technique and a GA-SVM Classifier Approach by Sabah Kouachi, Nacerdine Bourouba, Kamel Mebarkia, Imad Laidani

“…One of these troubleshoots faced is the lack of effective features that help to optimize fault classifier and hence improve circuit fault detection and identification. …”
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Fast Spectral Correlation Based on Sparse Representation Self-Learning Dictionary and Its Application in Fault Diagnosis of Rotating Machinery by Hongchao Wang, Wenliao Du

“…To address the above problems, an impulsive feature-enhanced method which combines fast spectral correlation (FSC) with sparse representation self-learning dictionary is proposed in the paper. …”
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Improved YOLOv8 Algorithm was Used to Segment Cucumber Seedlings Under Complex Artificial Light Conditions by Duokuo Zhang, Na Li, Mingfu Zhao, Kun Xu

“…Aiming at the challenging problem of cucumber seedling leaf segmentation under a complex artificial lighting environment, this study proposes an improved complex lighting YOLOv8 (CL-YOLOv8) model based on YOLOv8. …”
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Lexical Emergence on Reddit: An Analysis of Lexical Change on the “Front Page of the Internet” by Hanna Mahler

“…Secondly, words being attested in a representative corpus was proposed as a more realistic criterion for classifying a word as ‘established’ compared to its inclusion in standard dictionaries. A third problem is that the methodology only allows for the detection of single-word units, which is not an accurate representation of the changes taking place, as several of the emerging lexemes appear to be part of compounds.…”
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Two-dimensional spatial orientation relation recognition between image objects by Gong Peiyong, Zheng Kai, Jiang Yi, Zhao Huixuan, Huai Honghao, Guan Ruijie

“…A dedicated fusion module synthesizes features from both branches, generating a structured triple list that documents detected objects, their inter-object spatial orientations, and associated confidence scores. …”
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EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation by Suwicha Jirayucharoensak, Setha Pan-Ngum, Pasin Israsena

“…To alleviate overfitting problem, principal component analysis (PCA) is applied to extract the most important components of initial input features. …”
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Human Action Recognition Based on The Skeletal Pairwise Dissimilarity by E.E. Surkov, O.S. Seredin, A.V. Kopylov

“…A convolutional neural network based on the ResNetV2 with the SE-block is proposed to solve the activity recognition problem. SE-block allows to detect inter-channel dependencies and selecting the most important features. …”
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Point Data Registration With the Multi-Object, Cardinalized Optimal Linear Assignment Metric by Pablo A. Barrios, Vicente Guzman, Martin D. Adams, Claudio A. Perez

“…This allows robust scan registration to take place in the presence of unknown point correspondences and inter-scan translation and orientation as well as point cloud detection and spatial errors. The resulting Particle Swarm Optimization (PSO)-COLA registration algorithm is capable of determining inter-scan point correspondences, but can also run based on point correspondences determined by other algorithms, such as the application of Fast Point Feature Histograms (FPFH) descriptors. …”
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