Disordered-guiding photonic chip enabled high-dimensional light field detection by Zhijuan Gu, Weilun Zhang, Yu Yu, Xinliang Zhang

“…The disordered region introduces complex interference and scattering among polarized components, while the guiding region efficiently collects the outputs to on-chip photodetectors. …”
Get full text

Ensemble learning for multi-class COVID-19 detection from big data. by Sarah Kaleem, Adnan Sohail, Muhammad Usman Tariq, Muhammad Babar, Basit Qureshi

“…Although existing techniques are useful for detecting COVID-19 using X-rays, there is a need for further improvement in efficiency, particularly in terms of training and execution time. …”
Get full text

Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection by Sixu Guo, Jiyou Fei, Liying Wang, Hua Li, Xiaodong Liu

“…Vision-based rail defect detection plays a crucial role in ensuring the safety and efficiency of railway transportation systems. …”
Get full text

The effects of using BIM in detecting building design conflicts on architectural design products by Awder Omer Ali 1, a, *, Prof. Dr. Amjad Muhammed Ali Qaradaghi 2, a

“…The construction sector has recently begun to more efficiently integrate information technology into its design, building, and operations processes. …”
Get full text

Emerging biomarkers for early cancer detection and diagnosis: challenges, innovations, and clinical perspectives by Sameen Zafar, Amna Hafeez, Hania Shah, Iqra Mutiullah, Arslan Ali, Khushbukhat Khan, Gabriela Figueroa-González, Octavio Daniel Reyes-Hernández, Laura Itzel Quintas-Granados, Sheila I. Peña-Corona, Lashyn N. Kiyekbayeva, Monica Butnariu, Cristina-Elena Tota, Angela Caunii, Dietrich Büsselberg, Javad Sharifi-Rad, Gerardo Leyva-Gómez

“…Abstract Early detection and accurate cancer diagnosis are crucial for improving patient outcomes and survival rates. …”
Get full text

Comparative analysis of automated foul detection in football using deep learning architectures by Abdallah Rabee, Zakaria Anwar, Ahmed AbdelMoety, Ahmed Abdelsallam, Mahmoud Ali

“…This study presents a comprehensive comparative evaluation of eight state-of-the-art Deep Learning (DL) architectures — EfficientNetV2, ResNet50, VGG16, Xception, InceptionV3, MobileNetV2, InceptionResNetV2, and DenseNet121 — applied to the task of automated foul detection in football. …”
Get full text

Detecting Alzheimer's Based on MRI Medical Images by Using External Attention Transformer by Farrel Ardannur Deswanto, Isman Kurniawan

“…It enhances image classification by using two shared external memories and an attention mechanism that filters out redundant information for improved performance and efficiency. The aim of this research is to evaluate and compare the performance of the baseline Convolutional Neural Network (CNN) model, the Vision Transformer (ViT) model, and the EAT model in detecting Alzheimer's using a dataset of 6400 brain MRI images. …”
Get full text

Effects of Hybridizing the U-Net Neural Network in Traffic Lane Detection Process by Aron Csato, Florin Mariasiu

“…Similarly, in the Carla dataset (known for the complexity of the generated images), a substantial improvement was recorded, with an increase of +8.0% in mIoU and +5.7% in F1 score, showing better adaptability of the model to geometric structures in complex images. …”
Get full text

RGB and RGNIR image dataset for machine learning in plastic waste detectionZENODO by Owen Tamin, Ervin Gubin Moung, Jamal Ahmad Dargham, Samsul Ariffin Abdul Karim, Ashraf Osman Ibrahim, Nada Adam, Hadia Abdelgader Osman

“…While spectral imaging offers a promising solution, it has several drawbacks, such as complexity, high cost, and limited spatial resolution. …”
Get full text

Fault Detection in Gearboxes Using Fisher Criterion and Adaptive Neuro-Fuzzy Inference by Houssem Habbouche, Tarak Benkedjouh, Yassine Amirat, Mohamed Benbouzid

“…Consequently, deploying expert methods for fault detection and diagnosis is crucial to ensuring the reliability and efficiency of these systems. …”
Get full text

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

“…The multicore initiator module C2f_PKI is employed to replace C2f as the Backbone network to accelerate target detection and reduce model complexity. By incorporating FDPN and DASI fusion modules into the Head module section, the aim is to reduce model complexity and enhance detection accuracy. …”
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

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

“…It has two primary types: one-stage detectors known for their high speed and efficiency, and two-stage detectors, which offer higher accuracy but are often slower due to their complex architecture. …”
Get full text

LiDAR-Based Detection of Urban Trees Using a Backpack System by M. F. da Silva, L. F. Castanheiro, A. M. G. Tommaselli, A. M. G. Tommaselli, R. C. dos Santos, R. C. dos Santos, M. Galo, M. Galo

“…The sensor’s effective range is up to 50 m (at 80% reflectivity), enabling the acquisition of high-density point clouds at close-range distances while maintaining efficiency and accessibility in complex urban environments. …”
Get full text

AFHNet: Attention-Free Hybrid Network for Salient Object Detection in Underwater Images by Qian Tang, Zhen Wang, Xuqi Wang, Shan-Wen Zhang

“…However, traditional machine vision and deep learning approaches face notable challenges in complex underwater environments due to issues such as light attenuation, scattering, motion blur, color distortion, noise, low contrast, and multipath effects, which severely affect detection accuracy. …”
Get full text

RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection by Zhong Wang, Lanfang Lei, Tong Li, Xian Zu, Peibei Shi

“…Unlike generic object detection, smoke detection faces unique challenges due to smoke’s semitransparent, fluid nature, which often leads to false positives in complex backgrounds and missed detections—particularly around smoke edges and small targets. …”
Get full text

Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

“…Compared with existing detection methods, this approach shows outstanding performance in detection accuracy, localization precision, and computational efficiency, particularly excelling in small object detection.…”
Get full text

An Image-Free Single-Pixel Detection System for Adaptive Multi-Target Tracking by Yicheng Peng, Jianing Yang, Yuhao Feng, Shijie Yu, Fei Xing, Ting Sun

“…Conventional vision-based sensors face limitations such as low update rates, restricted applicability, and insufficient robustness in dynamic environments with complex object motions. Single-pixel tracking systems offer high efficiency and minimal data redundancy by directly acquiring target positions without full-image reconstruction. …”
Get full text

Seedling Stage Corn Line Detection Method Based on Improved YOLOv8 by LI Hongbo, TIAN Xin, RUAN Zhiwen, LIU Shaowen, REN Weiqi, SU Zhongbin, GAO Rui, KONG Qingming

“…However, traditional detection methods struggle to maintain high accuracy and efficiency under challenging conditions, such as strong light exposure and weed interference. …”
Get full text

Research on detection of wheat tillers in natural environment based on YOLOv8-MRF by Min Liang, Yuchen Zhang, Jian Zhou, Fengcheng Shi, Zhiqiang Wang, Yu Lin, Liang Zhang, Yaxi Liu

“…To bolster agricultural efficiency and precision, this study introduces the YOLOv8-MRF model (multi-path coordinate attention, receptive field attention convolution, and Focaler-CIoU-optimized YOLOv8), a groundbreaking advancement in automated detection of wheat tillers. …”
Get full text