Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
Get full text

Image forgery detection algorithm based on U-shaped detection network by Zhuzhu WANG

“…Aiming at the defects of traditional image tampering detection algorithm relying on single image attribute,low applicability and current high time-complexity detection algorithm based on deep learning,an U-shaped detection network image forgery detection algorithm was proposed.Firstly,the multi-stage feature information in the image by using the continuous convolution layers and the max-pooling layers was extracted by U-shaped detection network,and then the obtained feature information to the resolution of the input image through the upsampling operation was restored.At the same time,in order to ensure higher detection accuracy while extracting high-level semantic information of the image,the output features of each stage in U-shaped detection network would be merged with the corresponding output features through the upsampling layer.Further the hidden feature information between tampered and un-tampered regions in the image upon the characteristics of the general network was explored by U-shaped detection network,which could be realized quickly by using its end-to-end network structure and extracting the attributes of strong correlation information among image contexts that could ensure high-precision detection results.Finally,the conditional random field was used to optimize the output of the U-shaped detection network to obtain a more exact detection results.The experimental results show that the proposed algorithm outperforms those traditional forgery detection algorithms based on single image attribute and the current deep learning-based detection algorithm,and has good robustness.…”
Get full text

BeSnake: A Routing Algorithm for Scalable Spin-Qubit Architectures by Nikiforos Paraskevopoulos, Carmen G. Almudever, Sebastian Feld

“…It also has the option to adjust the level of optimization and to dynamically tackle parallelized routing tasks, all the while maintaining noise awareness. …”
Get full text

Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

Get full text

Gray Wolf Optimizer With Communication Strategy Based on DV-Hop for Nodes Location of Wireless Sensor Networks by Dan Yu, Ting Yuan, Haiyin Qing, Wenwu Xie, Peng Zhu

“…Comprehensive experimental analyses on established benchmark functions have validated the efficacy of the IGWO-CS method, illustrating its competitiveness with other advanced algorithms such as the Ranking-based Adaptive Cuckoo Search (RACS) and Modified Particle Swarm Optimization (MPSO). …”
Get full text

Optimization of spline parameters in approximation of multivalued functions by D. A. Karpov, V. I. Struchenkov

“…The spline parameters were optimized using a new mathematical model in the form of a modified Lagrange function and a special nonlinear programming algorithm. …”
Get full text

Solving synchromodal container transportation problem using a genetic algorithm by Ananthakrishnan Vaikkathe, Abdelhamid Benaini, Jaouad Boukachour

“…This paper proposes a Genetic Algorithm(GA) to solve the synchromodal transportation problem. …”
Get full text

A Review on Automated Detection and Identification Algorithms for Highway Pavement Distress by Zhenglong Lv, Zhexin Hao, Yuhan Zhu, Cong Lu

Get full text

Application of Immune Complement Algorithm to NSL-KDD Intrusion Detection Dataset by Mafaz Khalil Alanezi, Najlaa Aldabagh

“…<span>Many real world problems involve the simultaneous optimization of various and often conflicting objectives. …”
Get full text

Key Generation in Cryptography Using Elliptic-Curve Cryptography and Genetic Algorithm by Sanjay Kumar, Deepmala Sharma

“…In this context, this research introduces a novel approach to ECC-key-pair generation by utilizing genetic algorithms (GAs). GAs have proven effective in solving optimization problems by mimicking the principles of natural selection and genetics. …”
Get full text

Model for virtual corporations partner selection based on adaptive genetic algorithm by LI Jian1, JING Bo2, NIU Shao-zhang1, YANG Yi-xian1

“…To enhance the efficiency of corporation partner selection and optimization process in virtual corporations, an partner selection process and optimizations model for virtual corporations based on adaptive genetic algorithm were pre-sented. …”
Get full text

Beamforming algorithm for cognitive satellite and terrestrial network based on UAV relay by Yanli LI, Zhi LIN, Zining WANG, Ba XU, Ming CHENG, Jian OUYANG

“…Two beamforming (BF) schemes to achieve spectrum sharing by suppressing inter-system interferences in cognitive satellite and terrestrial networks were proposed, where the satellite and UAV cooperative network was used as the secondary network, while the terrestrial network was used as the primary network.Specifically, considering that only the statistical channel state information was available, a constrained optimization problem was formulated to maximize the signal-to- interference-plus-noise ratio of the secondary user under the constraints of the maximum transmit power at the UAV and the interference power of the primary user.Then, an iteration-based BF scheme was proposed to solve the constrained optimization problem.To reduce the computational complexity of the iterative algorithm, a zero-forcing based BF scheme was further proposed.Finally, computer simulations verify the correctness and effectiveness of the proposed BF schemes.…”
Get full text

Quantum Circuit Synthesis Using Fuzzy-Logic-Assisted Genetic Algorithms by Ishraq Islam, Vinayak Jha, Sneha Thomas, Kieran F. Egan, Alvir Nobel, Serom Kim, Manu Chaudhary, Sunday Ogundele, Dylan Kneidel, Ben Phillips, Manish Singh, Kareem El-Araby, Devon Bontrager, Esam El-Araby

“…Therefore, interest has grown towards heuristics-based synthesis techniques, which are able to produce approximations of the desired algorithm, while optimizing depth and gate-count. In this work, we investigate using genetic algorithms (GA)—a proven gradient-free optimization technique based on natural selection—for circuit synthesis. …”
Get full text

FDR coding and decoding algorithm for reliable transmission in underwater acoustic network by Lijuan WANG, Xiujuan DU, Chong LI

“…By analyzing the shortcomings of RLT coding and decoding algorithm,a filtering dimension reduction (FDR) algorithm was proposed,which eliminated the waiting time of the traditional decoding algorithm and achieves fast decoding.In addition,XOR operation between encoded packages effectively increased the number of one-degree encoded packages,and improved decoding probability while reducing transmission delay.An optimized degree distribution function for FDR decoding algorithm was proposed,which increased the proportion of two-degree,three-degree and four-degree encoded packages,further increased the probability of one-degree packet,so that speeded up the decoding progress.Simulation results with NS3 show that the decoding success probability of FDR algorithms higher than RLT algorithm.…”
Get full text

EAQR: A Multiagent Q-Learning Algorithm for Coordination of Multiple Agents by Zhen Zhang, Dongqing Wang

“…Experimental results show that EAQR outperforms the other algorithms in the box-pushing problem and achieves the theoretical optimal performance in the distributed sensor network problem.…”
Get full text

Case Study of Genetic Algorithms in Metrology: Assessment of Inter-laboratory Comparisons by Coulon Romain

“…The Genetic Algorithm (GA), a novel optimization-based approach, demonstrates exceptional resilience to outliers. …”
Get full text

Scalable PBFT-like algorithm for trust management of degree/graduation certificates by ZHANG Xuewang, LEI Zhitao, LIN Jinzhao

“…Analysis and simulation experiments demonstrate that the proposed algorithm ensures security while achieving higher throughput and scalability in large-scale applications of degree/graduation certificate trust management.…”
Get full text

Bias-field digitized counterdiabatic quantum optimization by Alejandro Gomez Cadavid, Archismita Dalal, Anton Simen, Enrique Solano, Narendra N. Hegade

“…We introduce a method for solving combinatorial optimization problems on digital quantum computers, where we incorporate auxiliary counterdiabatic (CD) terms into the adiabatic Hamiltonian, while integrating bias terms derived from an iterative digitized counterdiabatic quantum algorithm. …”
Get full text

Mine underground object detection algorithm based on TTFNet and anchor-free by Song Zhen, Qing Xuwen, Zhou Meng, Men Yuting

“…To solve the problem of poor object detection effect caused by uneven light and high noise in underground mines, this study proposes a TTFNet (training-time-friendly network)-based object detection algorithm for underground mines. First, CenterNet and TTFNet algorithms are introduced, then pooling is introduced into CSPNet basic structure to design a lightweight feature extraction network, at the same time optimizing the feature fusion way in the original algorithm, optimizing residual shrinkage network structure, and introducing it into object detection task. …”
Get full text

Observation optimization for marine target tracking by airborne and maritime unmanned platforms cooperation using adaptive enhanced dung beetle optimization by Qiuyang Dai, Faxing Lu, Haoran Shi, Junfei Xu, Jianjing Qu

“…Existing research predominantly focuses on homogeneous platform cooperative observation optimization under random error influences, while neglecting the collaborative optimization challenges of heterogeneous platforms affected by systematic errors. …”
Get full text