DeepGuard: Enhancing Violence Detection in Smart Cities Through Deep Learning by Md. Al-Mamun Provath, Musfequa Rahman, Kaushik Deb, Pranab Kumar Dhar, Tetsuya Shimamura

“…In addition, a custom keyframe extraction algorithm was designed, using temporal and pixel-level features to improve stability and accuracy. …”
Get full text

Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…Specifically, the TD3 algorithm, featuring a dual-critic structure, is employed to enhance control precision within predefined state and action spaces. …”
Get full text

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

Binary Large Object-Based Approach for QR Code Detection in Uncontrolled Environments by Omar Lopez-Rincon, Oleg Starostenko, Vicente Alarcon-Aquino, Juan C. Galan-Hernandez

“…The proposal consists in recognizing geometrical features of QR code using a binary large object- (BLOB-) based algorithm with subsequent iterative filtering QR symbol position detection patterns that do not require complex processing and training of classifiers frequently used for these purposes. …”
Get full text

Fish Disease Detection Using Image Based Machine Learning Technique in Aquaculture by Md Shoaib Ahmed, Tanjim Taharat Aurpa, Md. Abul Kalam Azad

Get full text

G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…First, a channel and spatial attention mechanism is introduced to improve the network’s capability to extract target features, significantly enhancing grasp detection performance in complex backgrounds. …”
Get full text

Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…Change detection in synthetic aperture radar imagery is challenging due to noise, complex nonlinear features, and variations in underlying data distributions. …”
Get full text

Cluster Workload Allocation: A Predictive Approach Leveraging Machine Learning Efficiency by Leszek Sliwko

“…This research investigates how Machine Learning (ML) algorithms can assist in workload allocation strategies by detecting tasks with node affinity operators (referred to as constraint operators), which constrain their execution to a limited number of nodes. …”
Get full text

Multimodal ultrasound deep learning to detect fibrosis in early chronic kidney disease by Xiachuan Qin, Xiaoling Liu, Linlin Xia, Qi Luo, Chaoxue Zhang

Get full text

Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data by H. T. Rüdisser, A. Windisch, U. V. Amerstorfer, C. Möstl, T. Amerstorfer, R. L. Bailey, M. A. Reiss

“…Out of the 640 ICMEs, 466 were detected correctly by our algorithm, producing a total of 254 false positives. …”
Get full text

ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…We propose an improved multistage identification model for strawberry based on the YOLOv9 algorithm—the ASHM-YOLOv9 model. The original YOLOv9 showed limitations in detecting strawberries at different growth stages, particularly lower precision in identifying occluded fruits and immature stages. …”
Get full text

From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision supportResearch in context by Sijm H. Noteboom, Eline Kho, Maria Galanty, Clara I. Sánchez, Frans C.P. ten Bookum, Denise P. Veelo, Alexander P.J. Vlaar, Björn J.P. van der Ster

“…Summary: Background: Clinical decision-making is increasingly shifting towards data-driven approaches and requires large databases to develop state-of-the-art algorithms for diagnosing, detecting and predicting diseases. …”
Get full text

Image Fusion and Target Detection Based on Dual ResNet for Power Sensing Equipment by Jie Yang, Wei Yan, Shuai Yuan, Yu Yu, Zheng Mao, Rui Chen

“…The image is preprocessed to a certain extent, using edge detection algorithms and corner detection algorithms to extract relatively stable feature points, and the feature vectors with excessive gradient values in the normalized visible light image are truncated and normalized again to eliminate the influence of nonlinear lighting. …”
Get full text

Features of tactics of inspection of accident sites in the investigation of illegal interference in the activities of energy facilities using unmanned vehicles by S. L. Kislenko, A. B. Smushkin

Get full text

Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers by Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim

“…Using the Pearson Correlation Coefficient, we extracted the most relevant features from the BoT–IoT dataset. After rigorous preprocessing, we used these data to train our algorithms. …”
Get full text

基于透视不变二值特征描述子的图像匹配算法 by Li-chuan GENG, Song-zhi SU, Shao-zi LI

“…Current local feature based image matching algorithms are usually less robust to image perspective transformation.Aiming to solve this problem，a new perspective invariant binary code (PIBC) based image matching algorithm is proposed.Firstly，FAST corners are detected on the pyramid images，those corners with non-maximum Harris corner response value and the edge points are further eliminated.And then，by simulating the perspective transformations of images taken from different viewpoints，a single FAST corner is described with binary descriptors under different viewpoint transformations，which makes the descriptor could describe the identical feature point on different perspective transform images.Experimental results show its robustness to image perspective transformation，while its complexity is similar with SURF.…”
Get full text

基于透视不变二值特征描述子的图像匹配算法 by Li-chuan GENG, Song-zhi SU, Shao-zi LI

“…Current local feature based image matching algorithms are usually less robust to image perspective transformation.Aiming to solve this problem，a new perspective invariant binary code (PIBC) based image matching algorithm is proposed.Firstly，FAST corners are detected on the pyramid images，those corners with non-maximum Harris corner response value and the edge points are further eliminated.And then，by simulating the perspective transformations of images taken from different viewpoints，a single FAST corner is described with binary descriptors under different viewpoint transformations，which makes the descriptor could describe the identical feature point on different perspective transform images.Experimental results show its robustness to image perspective transformation，while its complexity is similar with SURF.…”
Get full text

Segmentation Studies on Al‐Si‐Mg Metallographic Images Using Various Different Deep Learning Algorithms and Loss Functions by Abeyram M. Nithin, Murukessan Perumal, M. J. Davidson, M. Srinivas, C. S. P. Rao, Katika Harikrishna, Jayant Jagtap, Abhijit Bhowmik, A. Johnson Santhosh

“…ABSTRACT Segmenting metallographic pictures is being done in material science and related domains in order to detect the features within them. Therefore, it becomes crucial to find grains and secondary phase particles. …”
Get full text

PPLA-Transformer: An Efficient Transformer for Defect Detection with Linear Attention Based on Pyramid Pooling by Xiaona Song, Yubo Tian, Haichao Liu, Lijun Wang, Jinxing Niu

“…Deep learning-based algorithms for surface defect detection have been increasingly applied to industrial production processes. …”
Get full text

Snow depth estimation in Northeast China based on space-borne scatterometer data and ML model with optimal features by Wenfei Chen, Lingjia Gu, Xiaofeng Li, Xintong Fan

“…The multiple correlation coefficient feature selection (MCCFS) algorithm proposed in this study can effectively eliminate redundant features by retaining the features that have the most significant impact on SD estimation. …”
Get full text