Detection of Indoor Building Lighting Fixtures in Point Cloud Data using SDBSCAN by Humairah Mansor, Shazmin Aniza Abdul Shukor, Razak Wong Chen Keng, Nurul Syahirah Khalid

“…It is expected that the developed algorithm can be used to detect and classify fixtures from any 3D point cloud data representing buildings.…”
Get full text

Developing a Machine Vision System to Detect Weeds from Potato Plant by Yousef Abbaspour Gılandeh, Hossein Javadıkıa, Sajad Sabzı

Get full text

YOLO-HVS: Infrared Small Target Detection Inspired by the Human Visual System by Xiaoge Wang, Yunlong Sheng, Qun Hao, Haiyuan Hou, Suzhen Nie

“…To address challenges of background interference and limited multi-scale feature extraction in infrared small target detection, this paper proposes a YOLO-HVS detection algorithm inspired by the human visual system. …”
Get full text

Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…These additions help achieve an initial reduction in model size while preserving detection accuracy. Furthermore, we optimize the model by removing redundant parameters using the DepGraph pruning algorithm, which facilitates its application on edge devices. …”
Get full text

A Deep Reinforcement Learning Framework for Detecting Fraudulent Bank Account Openings by Abdul Qayoom, Wu Yadong, Wang Song, Sammar Abbas, Nadeem Ghafoor

“…Our proposed model achieved the highest fraud detection accuracy with 97% using the DQN algorithm with the benchmark Kaggle dataset for bank account fraud detection. …”
Get full text

Needle detection and localisation for robot‐assisted subretinal injection using deep learning by Mingchuan Zhou, Xiangyu Guo, Matthias Grimm, Elias Lochner, Zhongliang Jiang, Abouzar Eslami, Juan Ye, Nassir Navab, Alois Knoll, Mohammad Ali Nasseri

“…The algorithm was evaluated by comparing the depth of the top and bottom edge of the predicted bounding box to the ground truth. …”
Get full text

Detection of AI-Generated Texts: A Bi-LSTM and Attention-Based Approach by John Blake, Abu Saleh Musa Miah, Krzysztof Kredens, Jungpil Shin

“…This paper presents a novel algorithm that leverages cutting-edge machine-learning techniques to accurately and efficiently detect AI-generated texts. …”
Get full text

An optimized multi-task contrastive learning framework for HIFU lesion detection and segmentation by Matineh Zavar, Hamid Reza Ghaffari, Hamid Tabatabaee

“…To address these challenges, this paper introduces an innovative framework called the Optimized Multi-Task Contrastive Learning Framework (OMCLF), which leverages self-supervised learning (SSL) and genetic algorithms (GA) to enhance HIFU lesion detection and segmentation. …”
Get full text

Overcoming data scarcity in life-threatening arrhythmia detection through transfer learning by Giuliana Monachino, Beatrice Zanchi, Michael Wand, Giulio Conte, Athina Tzovara, Francesca Dalia Faraci

“…One of the main challenges in building robust LTA detection algorithms is the limited availability of labeled LTA data. …”
Get full text

Detection and Optimization of Photovoltaic Arrays’ Tilt Angles Using Remote Sensing Data by Niko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak

“…This paper presents a novel method for optimizing the tilt angles of existing PV arrays by integrating Very High Resolution (VHR) satellite imagery and airborne Light Detection and Ranging (LiDAR) data. At first, semantic segmentation of VHR imagery using a deep learning model is performed in order to detect PV modules. …”
Get full text

On Detection of Sybil Attack in Large-Scale VANETs Using Spider-Monkey Technique by Celestine Iwendi, Mueen Uddin, James A. Ansere, P. Nkurunziza, J. H. Anajemba, Ali Kashif Bashir

“…It performs better over long transmission distances for the detection of Sybil in dynamic VANETs’ system in terms of measurement precision, intrusion detection rate, and energy efficiency.…”
Get full text

Redundancy and conflict detection method for label-based data flow control policy by Rongna XIE, Xiaonan FAN, Suzhe LI, Yuxin HUANG, Guozhen SHI

“…To address the challenge of redundancy and conflict detection in the label-based data flow control mechanism, a label description method based on atomic operations has been proposed.When the label is changed, there is unavoidable redundancy or conflict between the new label and the existing label.How to carry out redundancy and conflict detection is an urgent problem in the label-based data flow control mechanism.To address the above problem, a label description method was proposed based on atomic operation.The object label was generated by the logical combination of multiple atomic tags, and the atomic tag was used to describe the minimum security requirement.The above label description method realized the simplicity and richness of label description.To enhance the detection efficiency and reduce the difficulty of redundancy and conflict detection, a method based on the correlation of sets in labels was introduced.Moreover, based on the detection results of atomic tags and their logical relationships, redundancy and conflict detection of object labels was carried out, further improving the overall detection efficiency.Redundancy and conflict detection of atomic tags was based on the relationships between the operations contained in different atomic tags.If different atomic tags contained the same operation, the detection was performed by analyzing the relationship between subject attributes, environmental attributes, and rule types in the atomic tags.On the other hand, if different atomic tags contained different operations without any relationship between them, there was no redundancy or conflict.If there was a partial order relationship between the operations in the atomic tags, the detection was performed by analyzing the partial order relationship of different operations, and the relationship between subject attribute, environment attribute, and rule types in different atomic tags.The performance of the redundancy and conflict detection algorithm proposed is analyzed theoretically and experimentally, and the influence of the number and complexity of atomic tags on the detection performance is verified through experiments.…”
Get full text

A Fault Detection Framework for Rotating Machinery with a Spectrogram and Convolutional Autoencoder by Hoyeon Lee, Jaehong Yu

“…Finally, we construct the fault detection model by applying the one-class classification algorithm to the latent feature vectors of training signals. …”
Get full text

Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…To monitor the drilling process in real time and enhance the efficiency of target detection at underground coal mine drill sites, an improved algorithm based on Yolov8n has been proposed, which offers advantages compared with the traditional detection methods. …”
Get full text

Tea Disease Detection Method Based on Improved YOLOv8 in Complex Background by Junchen Ai, Yadong Li, Shengxiang Gao, Rongsheng Hu, Wengang Che

“…Experimental results show that the proposed YOLO-SSM algorithm has obvious advantages in accuracy and model complexity and can provide reliable theoretical support for efficient and accurate detection and identification of tea leaf diseases in natural scenes.…”
Get full text

A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…The unique characteristics of 5G networks, while enabling advanced communication, present challenges in distinguishing between legitimate and malicious traffic, making it more difficult to detect anonymous traffic. Current methodologies for intrusion detection within 5G communication exhibit limitations in accuracy, efficiency, and adaptability to evolving network conditions. …”
Get full text

Enhanced UAV Detection and Classification With Birds Using NLFM Pulse-Doppler Radar by Ju-Hong Park, Yoo-Ho Jang, Sang-Hoon Kang, He-Won Jung, Seong-Ook Park

“…Detecting UAVs in clutter environments and classification with birds is a difficult and important problem. …”
Get full text

A photovoltaic anomaly data identification method based on image feature detection by QIU Yutao, ZHANG Lei, ZHOU Kaiyun, YAN Min, SUN Jintong, LONG Huan

“…To address this， this paper introduces an anomaly data identification algorithm based on image feature detection and dual-threshold processing. …”
Get full text

Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…Abstract Object detection is a fundamental task in computer vision. …”
Get full text

Deceptive Maneuvers: Subverting CNN-AdaBoost Model for Energy Theft Detection by Santosh Nirmal, Pramod Patil

“…Evasion attacks (EA) attempt to evade detection by misclassifying input data during testing. …”
Get full text