Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives by Simarjeet Kaur, Jimmy Singla, Lewis Nkenyereye, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Shaker El-Sappagh, Md. Saiful Islam, S. M. Riazul Islam

Get full text

Verification of color characteristics of document images captured in uncontrolled conditions by I.A. Kunina, O.A. Padas, O.A. Kolomyttseva

Get full text

A cooperative jamming mode adjustment method based on Multi-Agent reinforcement learning by Jieling Wang, Yanfei Liu, Chao Li, Dongdong Yang, Qingshan Yin

Get full text

Can machine-learning algorithms improve upon classical palaeoenvironmental reconstruction models? by P. Sun, P. B. Holden, H. J. B. Birks, H. J. B. Birks

Get full text

MIMO Detection for High Order QAM by Canonical Dual Approach by Ye Tian, Jr-Fong Dang

Get full text

Detection of Dashboard in Fuzzy Image by Correction Force Snake Model by YU Shu-chun, DONG Jing-yi

“…In order to solve the problem that the accuracy of the dashboard detection in fuzzy images is not high，an improved Snake model based on the correction force is proposed. …”
Get full text

PUE Attack Detection in CWSN Using Collaboration and Learning Behavior by Javier Blesa, Elena Romero, Alba Rozas, Alvaro Araujo, Octavio Nieto-Taladriz

“…Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. …”
Get full text

A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…Therefore, in this study, an improved YOLOv8 algorithm is proposed to address the problem of tomato fruit ripeness detection in complex scenarios, which is difficult to carry out accurately. …”
Get full text

Bankline extraction in remote sensing images using principal curves by Yun GUO, Yi-huai WANG, Chun-ping LIU, Sheng-rong GONG, Yi JI

“…In the learning process, the polygonal line (PL) algorithm and the error back propagation (BP) algorithm were combined. …”
Get full text

An anomaly detection scheme for data stream in cold chain logistics. by Zhibo Xie, Heng Long, Chengyi Ling, Yingjun Zhou, Yan Luo

“…But, because of the high cost and technical problem, the anomaly detection performance is poor, and the anomaly can not be detected in time, which affects the quality of goods. …”
Get full text

Study on the Lightweighting Strategy of Target Detection Model with Deep Learning by Junli Hu

“…Aiming at the high miss detection and false detection rate of traditional SSD (single shot multibox detector) target detection algorithm in target detection, this paper proposes a lightweight detection algorithm for deep learning target detection model in order to improve the detection accuracy. …”
Get full text

BLSTM based night-time wildfire detection from video. by Ahmet K Agirman, Kasim Tasdemir

“…To this end, a BLSTM based night-time wildfire event detection from a video algorithm is proposed. It is shown in the experiments that the proposed algorithm attains 95.15% of accuracy when tested against a wide variety of actual recordings of night-time wildfire incidents and 23.7 ms per frame detection time. …”
Get full text

Aviation Rivet Classification and Anomaly Detection Based on Deep Learning by Xiao-bo Zhu

“…And a method of aviation rivet classification and anomaly detection based on deep learning algorithm was proposed. …”
Get full text

Cross-Modal Fake News Detection Method Based on Multi-Level Fusion Without Evidence by Ping He, Hanxue Zhang, Shufu Cao, Yali Wu

Get full text

Spammer group detection based on cascading and clustering of core figures by Qianqian Jiang, Chunrong Zhang, Ning Li, Dickson K. W. Chiu, Xianwen Fang, Shujuan Ji

“…Abstract The problem of collaborative spamming in e-commerce is gradually increasing, and traditional spammer group detection algorithms usually seem cumbersome and time-consuming when dealing with massive user review data. …”
Get full text

On the Detection of Exploitation of Vulnerabilities Leading to the Execution of a Malicious Code by Yury V. Kosolapov

“…It is assumed that taking into account the distances between function calls will reveal shell code execution using system and / or library function calls. An algorithm and a system for detecting abnormal code execution are proposed. …”
Get full text

Research on Spread Spectrum Codes Optimized by Sparrow Search Algorithm and Extreme Gradient Boosting by LIANG Zhiru, BIAN Dongming, ZHANG Gengxin

“…The problem of spread code identification is transferred into a peak detection classification problem. …”
Get full text

Machine Learning- and Deep Learning-Based Multi-Model System for Hate Speech Detection on Facebook by Amna Naseeb, Muhammad Zain, Nisar Hussain, Amna Qasim, Fiaz Ahmad, Grigori Sidorov, Alexander Gelbukh

“…This study seeks to minimize this problem by developing an Arabic script-based tool for automatically detecting hate speech in Roman Urdu, an informal script used most commonly for South Asian digital communications. …”
Get full text

A similarity-based multi-objective test optimization technique using search algorithm by Amir Sohail Habib, Saif Ur Rehman Khan, Shahid Hussain, Naseem Ibrahim, Habib un Nisa, Abdullah Yousafzai

“…Hence, it is required to optimize the test suite by finding a diverse subset of test cases having high code coverage, fault-detection rate, and minimal execution time. Objective:: To solve the regression test optimization problem, the researchers have proposed various approaches including greedy algorithms, search-based algorithms, and clustering algorithms. …”
Get full text

Non-cooperative signal modulation recognition algorithm based on joint feature parameter extraction by Haifei SI, Xingliu HU, Zhen SHI, Shiyong LI

“…Aiming at the problem that in the current electromagnetic environment,the modulation method is complicated,the frequency-consuming equipment increases,the spectrum is congested,and the electromagnetic environment interference increases,the algorithm of OFDM signal detection and subcarrier identification in the background of non-cooperative communication were deeply studied.Using the different distribution states of OFDM signals and single carrier signals in the time domain,a joint characteristic parameter was proposed to solve the existence problem of OFDM in the received signal.For the phase shift and frequency offset problems caused by the channel transmission to the signal,by using the periodic stability the blind parameter estimation was performed to obtain the signal prior information.On the basis of the obtained signal prior information,a multi-level classification and recognition method for non-cooperative OFDM signal sub-carrier signals was proposed.Therefore,a model based on non-cooperative communication system OFDM signal detection and subcarrier modulation identification was designed,and finally modulation identification of unknown signals was completed.Simulation experiments show that in non-cooperative communication systems,OFDM signals and single-carrier signals can be accurately identified,and ideal modulation recognition effects can be achieved on empty subcarriers,QPSK,and 16QAM in the receiver OFDM signal subcarriers,overcoming the channel transmission band The problems of phase shift and frequency offset have improved the accuracy of modulation mode identification.…”
Get full text