Research on Lightweight Method of Insulator Target Detection Based on Improved SSD by Bing Zeng, Yu Zhou, Dilin He, Zhihao Zhou, Shitao Hao, Kexin Yi, Zhilong Li, Wenhua Zhang, Yunmin Xie

“…Aiming at the problems of a large volume, slow processing speed, and difficult deployment in the edge terminal, this paper proposes a lightweight insulator detection algorithm based on an improved SSD. Firstly, the original feature extraction network VGG-16 is replaced by a lightweight Ghost Module network to initially achieve the lightweight model. …”
Get full text

Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

“…In the proposed approach, the initial genetic data were first subjected to feature selection. <b>Results:</b> The target genes were screened and combined with data augmentation and ensemble boosting algorithms. …”
Get full text

Improvement of YOLO v8 Segmentation Algorithm and Its Study in the Identification of Hazards in Plateau Pika by Yaosheng Han, Yunpeng Jin, Chunmei Li, Xiangjie Huang

“…Secondly, the latest segmentation algorithm provided by YOLO v8 is improved to design a segmentation algorithm that can accurately detect the distribution of rodent infestation in the plateau scene. …”
Get full text

AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…Lung segmentation plays a pivotal role in the diagnostic pipeline, directly impacting the accuracy of disease detection and treatment planning. This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
Get full text

Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

Get full text

Function encoding based approach for App clone detection in cloud environment by Jia YANG, Cai FU, Lansheng HAN, Hongwei LU, Jingliang LIU

“…An efficient function-based encoding scheme in the cloud environment for detecting the cloned Apps was designed,called Pentagon.Firstly,a basic block feature extraction method was proposed.Secondly,a monotonic encoding algorithm for the App function was designed,which encoded the function based on the control flow graph structure and basic block attributes.Finally,a three-party libraries filtering method was proposed by using an efficient clustering algorithm based on the function feature.Experiments verified the effectiveness of the proposed scheme.The average search time is close to 79 ms,and the clone detection accuracy achieves 97.6%.…”
Get full text

Pavement pothole detection system based on deep learning and binocular vision by Tian Guan, Jianyuan Cai, Yu Wang, Wei Yang, Xiaobo Chang, Yi Han

“…The experimental results show that the model has better accuracy than the basic model and can effectively detect road potholes. In addition, we replaced the ordinary convolution in the CenterNet feature extraction network with pyramid convolution with multiple receptive fields, and designed a feature fusion module in the same network to fuse low-level and high-level features related to holes, thus establishing a PF-CenterNet that combines pyramid convolution with feature fusion to detect areas containing road potholes. …”
Get full text

Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…To optimize performance, we developed RF_WOA_DBO-an integrated algorithm combining RF with enhanced Whale Optimization Algorithm (WOA) for global feature selection and modified Dung Beetle Optimizer (DBO) for local parameter tuning. …”
Get full text

A method for synthetic speech detection using local phase quantization by Jia XU, Zhihua JIAN, Honghui JIN, Man YANG

“…Due to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward using the information in spectral domain of the synthetic speech spectrogram.The method employed the local phase quantization (LPQ) algorithm to describe frequency domain information in the speech spectrogram.Firstly, the spectrogram was divided into several sub-blocks, and then the LPQ was performed on each sub-block.After the histogram statistical analysis, the LPQ feature vector was obtained and used as the input feature of the random forest classifier to realize the synthetic speech detection.The experimental results demonstrate that the proposed method further reduces tandem detection cost function (t-DCF) and has better generalization ability.…”
Get full text

SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…This study proposes an enhanced SR-DETR algorithm aimed at improving the detection of individuals who have fallen overboard. …”
Get full text

RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…This study proposes an occluded object detection algorithm, RE-YOLOv5, based on receptive field enhancement to assist with the difficult identification of occluded objects in complex road environments. …”
Get full text

A Benchmark Dataset for Aircraft Detection in Optical Remote Sensing Imagery by Jianming Hu, Xiyang Zhi, Bingxian Zhang, Tianjun Shi, Qi Cui, Xiaogang Sun

“…The problem is that existing aircraft detection datasets rarely simultaneously consider the diversity of target features and the complexity of environmental factors, which has become an important factor restricting the effectiveness and reliability of aircraft detection algorithms. …”
Get full text

Bilingual hate speech detection on social media: Amharic and Afaan Oromo by Teshome Mulugeta Ababu, Michael Melese Woldeyohannis, Emuye Bawoke Getaneh

“…According to the experiment, BiLSTM with FastText feature extraction is an outperforming the other algorithm by achieving a 78.05% accuracy for Bilingual Amharic Afaan Oromo hate speech detection. …”
Get full text

Real-Time Fire Object Detection System Using Machine Learning by Akuthota Venkata Bhargavi., Syed Khadar Basha., Ramineni Dhanush., Guduru Vikram.

“…This paper introduces a fire object detection system that employs machine learning algorithms to enhance early detection of fire breakout and response to the same. …”
Get full text

Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…During the feature extraction stage, the algorithm employs a random unitary matrix transformation. …”
Get full text

Anomaly detection in virtual machine logs against irrelevant attribute interference. by Hao Zhang, Yun Zhou, Huahu Xu, Jiangang Shi, Xinhua Lin, Yiqin Gao

“…Firstly, the log parsing algorithm is used to parse the logs. Then, the feature extraction algorithm, which combines Long Short-Term Memory and Autoencoder-Decoder, is applied to extract features. …”
Get full text

ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning by Raiyan Jahangir, Muhammad Nazrul Islam, Md. Shofiqul Islam, Md. Motaharul Islam

“…Regular monitoring is essential for effective management, as early detection and timely treatment greatly improve survival outcomes. …”
Get full text

Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
Get full text

RQPool: A Novel Multi-Branch Graph-Level Anomaly Detection by Aaron Alex Philip, Ziad Kobti

“…Moreover, existing Graph Neural Network (GNN) algorithms focus primarily on spatial domain features while neglecting spectral properties. …”
Get full text

Spiking Residual ShuffleNet-Based Intrusion Detection in IoT Environment by Sneha Leela Jacob, H. Parveen Sultana

“…In this context, a new model called Spiking Residual ShuffleNet (SR-ShuffleNet) is introduced for intrusion detection (ID) in an IoT environment. The Multi-objective Fractional Artificial Bee Colony (MFABC) algorithm is used for routing. …”
Get full text