Spectrum sensing method based on residual dense network by Jianxin GAI, Xianfeng XUE, Ruixiang NAN, Jingyi WU

“…Aiming at the problem that the traditional spectrum sensing method based on convolutional neural network（CNN） did not make full use of image feature and the ability of extracting the image feature was limited by the shallow network structure， a spectrum sensing method based on the residual dense network （ResDenNet） was proposed.By adding dense connections in the traditional neural network， the information reuse of the image feature was achieved.Meanwhile， shortcut connections were employed at both ends of the dense unit to implement deeper network training.The spectrum sensing problem was transformed into the image binary classification problem.Firstly， the received signals were integrated into a matrix， which was normalized and transformed by gray level.The obtained gray level images were used as the input of the network.Then， the network was trained through dense learning and residual learning.Finally， the online data was input into the ResDenNet and spectrum sensing was implemented based on image classification.The numerical experiments show that the proposed method is superior to the traditional ones in terms of performance.When the SNR is as low as -19 dB， the detection probability of the proposed method is still high up to 0.96 with a low false alarm probability of 0.1， while a better generalization ability is displayed.…”
Get full text

Research on the Bearing Remaining Useful Life Prediction Method Based on Optimized BiLSTM by Yi Zou, Wenlei Sun, Tiantian Xu, Bingkai Wang

“…To solve these problems, a bearing RUL prediction method based on early degradation detection and optimized BiLSTM is proposed: an optimized VMD combined with the Pearson correlation coefficient is used to denoise the bearing signal. …”
Get full text

Steganalysis Using KL Transform and Radial Basis Neural Network by Safwan Hasoon, Farhad Khalifa

“…The essential problem in the security field is how to detect information hiding. …”
Get full text

Molecular Diagnosis In Infectious Keratitis by Venkatesh Prajna N, Lokeshwari A, Lalitha Prajna

“…Microbial keratitis is a very important public health problem in our country. The magnitude of the burden of this problem is not often fully understood and hence it is often termed as a “silent epidemic”. …”
Get full text

Defect Image Recognition and Classification for Eddy Current Testing of Titanium Plate Based on Convolutional Neural Network by Weiquan Deng, Jun Bao, Bo Ye

“…In the actual production environment, the eddy current imaging inspection of titanium plate defects is prone to scan shift, scale distortion, and noise interference in varying degrees, which leads to the defect false detection and even missed inspection. In view of this problem, a novel image recognition and classification method based on convolutional neural network (CNN) for eddy current detection of titanium plate defects is proposed. …”
Get full text

System Eliminating Emergency Discharges in Industrial Facilities Waste Waters Using Relative Signal Description by V. A. Alekseev, S. I. Yuran, V. P. Usoltsev, D. N. Shulmin

“…Thus, detecting these coagulates in real-time is a relevant problem.To solve this problem, the authors suggest building an automated system that shall record and identify the emergency harmful substances discharges to the industrial companies waste waters caused by accidents. …”
Get full text

Joint simplification of various types spatial objects while preserving topological relationships by Olga P. Yakimova, Dmitriy M. Murin, Vladislav G. Gorshkov

“…Considering coverings and mesh structures allows us to reduce the more general problem of topological conflict correction to the problem of resolving topological conflicts within a single mesh cell. …”
Get full text

Swin‐YOLOX for autonomous and accurate drone visual landing by Rongbin Chen, Ying Xu, Mohamad Sabri bin Sinal, Dongsheng Zhong, Xinru Li, Bo Li, Yadong Guo, Qingjia Luo

“…GPS‐based methods will not work in places where GPS signals are not available; multi‐sensor combination navigation is difficult to be widely used because of the high equipment requirements; traditional vision‐based methods are sensitive to scale transformation, background complexity and occlusion, which affect the detection performance. In this paper, we address these problems and apply deep learning methods to target detection in the UAV landing phase. …”
Get full text

DIFFERENCES BETWEEN PEDIATRIC PULMONARY AND EXTRA-PULMONARY TUBERCULOSIS: A WARNING SIGN FOR THE FUTURE by Ilker Devrim, Hüseyin Aktürk, Nuri Bayram, Hurşit Apa, Şener Tulumoğlu, Fatma Devrim, Ttulin Erdem, Gamze Gulfidan, Yüce Ayhan, Demet Can, Hüdaver Alper

“…Introduction: Tuberculosis (TB) remains a major global health problem affecting millions of people annually. Tuberculosis in children has unique features different from adults which makes the diagnosis to be more difficult. …”
Get full text

A Visual Measurement Method for Large-Sized Parts by Junkai Yang

“…The method utilizes the edge detection pixel point data of the part image for searching and region localization of line and circle features in the image with a modified Hough transform; A geometric calculation is used to compute the coordinates of the point cloud within the feature area; Drawing on the idea of graph neural network, the priori knowledge of machining is utilized to establish the correlation of related dimensional features in the part drawing, and this is used to propose a model of dimensional validation and correction by the combination of different features. …”
Get full text

Detección de situaciones de emergencias usando el modelo Naive- Bayes de machine learning. by Iván Leonel Vásquez-Rojas, Miguel José Vívas-Cortéz

“…Nowadays, social networks have gained ground in the generation and obtaining of information instantly, this feature makes it very useful in the detection and warnings of emergencies such as road accidents, fires, storms, floods, etc. …”
Get full text

Neural-Network-Based Synchronization Acquisition with Hankelization Preprocessing by Gyung-Eun Kim, Jung-Hwan Kim, Jong-Ho Lee, Woong-Hee Lee

“…In such environments, the usage of a long synchronization signal is beneficial for ensuring sufficient correlation information and enhancing detection robustness. To address these problems, this paper proposes a novel framework that combines Hankelization-based preprocessing with the operation of a neural network (NN). …”
Get full text

Deep Learning in Visual Computing and Signal Processing by Danfeng Xie, Lei Zhang, Li Bai

“…Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data. Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing. …”
Get full text

Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Unlike GSM, which scans raw pixels and lacks discriminative power, our LBP-based scheme is specifically designed to capture texture features relevant to spoofing detection. Additionally, transforming the input from the RGB space to the LBP space enhances robustness against adversarial noise. …”
Get full text

Deep Unified Model For Face Recognition Based on Convolution Neural Network and Edge Computing by Muhammad Zeeshan Khan, Saad Harous, Saleet Ul Hassan, Muhammad Usman Ghani Khan, Razi Iqbal, Shahid Mumtaz

“…Usually, for face recognition, scale-invariant feature transforms (SIFT) and speeded up robust features (SURF) have been used by the research community. …”
Get full text

Predicting soil organic carbon with ensemble learning techniques by using satellite images for precision farming by Shyamal Mundada, Pooja Jain

“…Abstract Soil plays a major role in the agricultural system. Soil composition detection can help farmers to take appropriate decision leading to proper crop growth. …”
Get full text

A lightweight semantic segmentation method for concrete bridge surface diseases based on improved DeeplabV3+ by Zhiyuan Yu, Chunquan Dai, Xiaoming Zeng, Yunlong Lv, Haisheng Li

“…Abstract Due to the similar features of different diseases and insufficient semantic information of small area diseases in the surface disease image of concrete bridges, the existing semantic segmentation models for identifying surface diseases in concrete bridges suffer from problems such as large number of parameters, insufficient feature extraction, and low segmentation accuracy. …”
Get full text

Automated Analysis of Thoracic Aortic Aneurysms Based on Chest Computed Tomography Data: a Population Study in Moscow by A. V. Solovev, Yu. A. Vasilev, V. E. Sinitsyn, A. V. Vladzymyrskyy, D. S. Semenov

“…For this reason, conducting new epidemiological studies on this problem in our country is relevant.Objective: to study the prevalence of pathological dilatation of the thoracic aorta in Moscow by means of artificial intelligence technologies (AITs) using chest computed tomography (CT) data.Material and methods. …”
Get full text

Laryngeal disease classification using voice data: Octave-band vs. mel-frequency filters by Jaemin Song, Hyunbum Kim, Yong Oh Lee

“…Mel Frequency Cepstral Coefficients (MFCCs) are widely used for voice analysis, but Octave Frequency Spectrum Energy (OFSE) may offer better accuracy in detecting subtle voice changes. Problem statement: Accurate early diagnosis of laryngeal cancer through voice data is challenging with current methods like MFCC. …”
Get full text

BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules by Sumiya Arafin, Adnan Ferdous Ashrafi, Md. Golam Rabiul Alam, Ashis Talukder

“…Here, we have deployed the feature extraction process. A Convolutional Block Attention Module (CBAM) was integrated into the Modified ResNet12 architecture. …”
Get full text