Tampered text detection via RGB and frequency relationship modeling by Yuxin WANG, Boqiang ZHANG, Hongtao XIE, Yongdong ZHANG

“…In recent years, the widespread dissemination of tampered text images on the Internet constitutes an important threat to the security of text images.However, the corresponding tampered text detection (TTD) methods have not been sufficiently explored.The TTD task aims to locate all text regions in an image while judging whether the text regions have been tampered with according to the authenticity of the texture.Thus, different from the general text detection task, TTD task further needs to perceive the fine-grained information for real-world and tampered text classification.TTD task has two main challenges.One the one hand, due to the high similarity in texture between real-world texts and tampered texts, TTD methods that only learn from RGB domain features have limited capability to distinguish these two-category texts well.On the other hand, as the different detecting difficulty exists in real-world texts and tampered texts, the network cannot well balance the learning process of the two-category texts, resulting in the imbalance detection performance between real-world and tampered texts.Compared with RGB domain features, the discontinuity of text texture in frequency domain can help the network to identify the authenticity of text instances.Accordingly, a new TTD method based on RGB and frequency information relationship modeling was proposed.The features in the RGB and frequency domains were extracted by independent feature extractors respectively.Thus, the identification ability of tampered texture can be enhanced by introducing frequency information during the texture perception.Then, a global RGB-frequency relationship module (GRM) was introduced to model the texture authenticity relationship between different text instances.GRM referred to the RGB-frequency features of other text instances in the same image to assist in judging the authenticity of the current text instance, which solved the problem of imbalanced detection performance.Furthermore, a new TTD dataset (Tampered-SROIE) was proposed to evaluate the effectiveness of proposed method, which contains 986 images (626 training images and 360 test images).By evaluating on the Tampered-SROIE, the proposed method obtains 95.97% and 96.80% in F-measure for real-world and tampered texts respectively and reduces the imbalanced detection accuracy by 1.13%.The proposed method will give new insights to the TTD community from the perspective of network structure and detection strategy.Tampered-SROIE also provides an evaluation benchmark for future TTD methods.…”
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An effective microscopic image augmentation approach by Wanying Li, Linhe Yang, Guobei Peng, Guangyao Pang, Zhenming Yu, Xiaoying Zhu

“…The approach consists of two aspects: first, we design the conditionally guided microscopic image generation model (CGMIGM), which combines the denoising diffusion probabilistic models (DDPM) based conditional guidance technique to efficiently generate rare features and thus alleviate the class imbalance problem. …”
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An Improved Correlation Filtering Method for Tracking Maritime Small Targets of GF-4 Staring Satellite Sequence Images by Deyang Zhang, Yao Xu, Haimin Hu

“…In this paper, GF-4 staring satellite’s sequence images are taken as the research objects, and its features such as “short imaging interval, long image sequence and high resolution” are used to solve the tracking problem of large and medium ships at sea. …”
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SOCIO-PSYCHOLOGICAL CHARACTERISTICS OF THE MODERN STUDENT by Y. V. Kukanova

“…However, despite the adaptation problems, the author points out the growth of self-consciousness and intention to defend their opinions as the distinctive feature of that social group, the self-esteem being the primary behavior regulator.…”
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ECG Paper Digitization and R Peaks Detection Using FFT by Ibraheam Fathail, Vaishali D. Bhagile

“…It is employed to investigate particular varieties of aberrant heart activity, such as arrhythmias and conduction problems. One of the most essential tools for detecting heart problems is the electrocardiogram (ECG). …”
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The Rise of Welfare Service States - Conceptual challenges of an ambiguous welfare settlement and the need for new policy research by Jean-Michel Bonvin, Hans-Uwe Otto, Arne Wohlfarth, Holger Ziegler

“…Therefore, principal problems of service-based welfare production with regard to the democratic quality of societies will be discussed: Problems of assessment, non-take-up, discretion, managerialism and paternalism. …”
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PRIORITY AND THE RIGHT OF PRIORITY IN PATENT LAW – A RIGHT WITH AN AMBIGUOUS NATURE AND SURPRISING EFFECTS by Viorel ROȘ, Andreea LIVĂDARIU

“…In other words, the scope of protection claimed in the subsequent application cannot be broader than that of the priority application. The problem, the solution, and the essential features of the invention later filed for patenting must be identical to those in the earlier application for the priority date to be validly claimed for the subsequent application. …”
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DCN-YOLO: A Small-Object Detection Paradigm for Remote Sensing Imagery Leveraging Dilated Convolutional Networks by Meilin Xie, Qiang Tang, Yuan Tian, Xubin Feng, Heng Shi, Wei Hao

“…To address this problem, we propose to use multi-scale dilated convolutions to increase the receptive field size of the model to adapt to changes in object size, capture multi-scale contextual information of the feature map, and extract richer object features. …”
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Development of Facility Rental, Product Shipment Tracking, and Payment in the UnilaHub Application by Aristoteles Aristoteles, Rifan Setiadi, Naufal Anbial Falah, M. Iqbal Parabi, Dwi Sakethi, Febi Eka Febriansyah, Ardiansyah Ardiansyah

“…This study aims to enhance UnilaHub by introducing new features like facility rental, product shipment tracking, and integrated payment systems. …”
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A Wi-Fi sensing method for complex continuous human activities based on CNN-BiGRU by Yang LIU, Anming DONG, Jiguo YU, Kai ZHAO, You ZHOU

“…Human activity sensing based on Wi-Fi channel state information (CSI) has an important application prospect in future intelligent interaction scenarios such as virtual reality, intelligent games, and the metaverse.Accurate sensing of complex and continuous human activities is an important challenge for Wi-Fi sensing.Convolutional neural network (CNN) has the ability of spatial feature extraction but is poor at modeling the temporal features of the data.While long short-term memory (LSTM) network or gated recurrent unit (GRU) network, which are suitable for modeling time-series data, neglect learning spatial features of data.In order to solve this problem, an improved CNN that integrates bidirectional gated recurrent unit (BiGRU) network was proposed.The bi-directional feature extraction ability of BiGRU was used to capture the correlation and dependence of the front and back information in the time series data.The extraction of the spatiotemporal features of the time series CSI data was realized, and then the mapping relationship between the action and the CSI data was present.Thus the recognition accuracy of the complex continuous action was improved.The proposed network structure was tested with basketball actions.The results show that the recognition accuracy of this method is above 95% under various conditions.Compared with the traditional multi-layer perceptron (MLP), CNN, LSTM, GRU, and attention based bidirectional long short-term memory (ABLSTM) baseline methods, the recognition accuracy has been improved by 1%～20%.…”
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Diagnosis of abnormal sound in loudspeakers by integrated attention mechanism convolutional neural network by ZHOU Jinglei, WANG Xiaoming, LI Limin

“…Secondly, the feature data was input into the 1DCNN-BiLSTM network for initial feature extraction. …”
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CURRENT CRIMINOLOGICAL SITUATION IN THE NORTH-CAUCASUS FEDERAL DISTRICT by A. Volkov, Y. Byshevsky

“…At the same time, the main emphasis is placed on the structural features of the state of crime and its causal complex. …”
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Predictive Modeling of Dairy Sales Using Multi-Perspective Fusion Bi-LSTM Integrated with Universal Scale CNN: Insights from the Dairy Supply Chain by Naveen D. Chandavarkar, Dr. Soumya S

“…The present research uses Universal Scale CNN, specifically 1D-CNN, that is able to acquiring the features in ideal and in effective rates. Followed by, the extracted features are fed as an input to Multi-Perspective based Bi-LSTM (Bidirectional Long Short Term Memory) that is able to acquiring the features in an effective manner in characteristics of reducing the error rates upon the prediction sales rate of dairy based products. …”
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Robust style injection for person image synthesis by Yan Huang, Jianjun Qian, Shumin Zhu, Jun Li, Jian Yang

“…RSI develops a simple and efficient cross‐attention based module to fuse the features of both source semantic styles and target pose for achieving the coarse aligned features. …”
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The emigrant prose of S.D. Dovlatov in the context of American ‘new journalism’ of the 1980s by Evgeniya Yu. Poselenova, Victoriya S. Monsh

“…The focus of research attention is concentrated on the features of the American ‘new journalism’ of the 1960s-80s, and the influence of its narrative and stylistic techniques on the prose and journalism of S.D. …”
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Efficient early-stage disease detection in pomegranate (Punica granatum) using convolutional neural networks optimized by honey badger optimization algorithm by Sameera P, Abhay A. Deshpande

“…The segmented image was subjected to feature extraction based on the identified features. …”
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Re-LSTM: A long short-term memory network text similarity algorithm based on weighted word embedding by Weidong Zhao, Xiaotong Liu, Jun Jing, Rongchang Xi

“…Natural language processing text similarity calculation is a crucial and difficult problem that enables matching between various messages. …”
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An Interpretable Method for Anomaly Detection in Multivariate Time Series Predictions by Shijie Tang, Yong Ding, Huiyong Wang

“…Our method transforms the interpretation of anomalous features into solving an optimization problem in a normal “reference” state. …”
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Fault Diagnosis of Wind Turbine Gearbox Based on Mel Spectrogram and Improved ResNeXt50 Model by Xiaojuan Zhang, Feixiang Jia, Yayu Chen

“…By adding the CBAM module in ResNeXt to enhance the model’s attention to important features and combining it with the Arcloss loss function to make the model learn more discriminative features, the generalization ability of the model is strengthened. …”
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Fast binary logistic regression by Nurdan Ayse Saran, Fatih Nar

“…Furthermore, to address the common problem of collinear features, we apply singular value decomposition (SVD), resulting in a low-rank representation commonly used to reduce computational complexity while preserving essential features and mitigating noise. …”
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