For Precision Animal Husbandry: Precise Detection of Specific Body Parts of Sika Deer Based on Improved YOLO11 by Jinfan Wei, Haotian Gong, Lan Luo, Lingyun Ni, Zhipeng Li, Juanjuan Fan, Tianli Hu, Ye Mu, Yu Sun, He Gong

“…The number of parameters is only 62% (5.9 million) of the original model, the computational load is 60% (12.8 GFLOPs) of the original model, and the average inference time is as low as 3.8 ms. This work provides strong algorithmic support for achieving non-contact intelligent monitoring of sika deer, assisting in automated management (deer antler collection and preparation), and improving animal welfare, demonstrating the application potential of deep learning technology in modern precision animal husbandry.…”
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A lightweight multi-deep learning framework for accurate diabetic retinopathy detection and multi-level severity identification by Amad Zafar, Kwang Su Kim, Muhammad Umair Ali, Jong Hyuk Byun, Jong Hyuk Byun, Seong-Han Kim

“…The online dataset is used to validate the proposed framework, and results show that the proposed model is lightweight and has comparatively low learnable parameters compared to others. The proposed two-stage framework enhances the classification performance, achieving a 99.06% classification rate for DR detection and an accuracy of 90.75% for DR severity identification for APTOS 2019 dataset.…”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…Lung cancer remains the leading cause of cancer-related mortality globally, largely due to late-stage diagnoses. While low-dose computed tomography (LDCT) has improved early detection and reduced mortality in high-risk populations, traditional screening strategies often adopt a one-size-fits-all approach based primarily on age and smoking history. …”
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Using a new algorithm in Machine learning Approaches to estimate level-of-service in hourly traffic flow data in vehicular ad hoc networks by Ahmed Ibrahim Turki, Saad Talib Hasson

“…This study proposes an algorithm for hourly LOS assessment by incorporating flow data provided by the MIDAS (Motorway Incident Detection and Automatic Signaling) system. …”
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A review of deep-learning-based models for afaan oromo fake news detection on social media networks by Kedir Lemma Arega, Kula Kekeba Tune, Asrat Mulatu Beyene, Wegderes Tariku, Nurhussen Menza Bune

“…The study aims to provide a comprehensive understanding of how deep-learning-based models can detect fake news in Afaan Oromo and address unique challenges in low-resource settings. …”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Its feature extraction module employs a dual-branch information residual unit (DIRU) as a substitute for the conventional convolution block, which combines the feature extraction capabilities of global pooling and max pooling, reducing the number of parameters while also achieving a certain improvement in detection results. In the feature fusion stage, it utilizes the attention-guided fusion module (AGFM), which can allow the attention information of high-level semantics to guide the low-level semantics, and simultaneously, adds a high-level semantic residual attention module (HSRA) to enhance the perception of defect shapes and improve detection effectiveness. …”
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Can Machine Learning Enhance Intrusion Detection to Safeguard Smart City Networks from Multi-Step Cyberattacks? by Jowaria Khan, Rana Elfakharany, Hiba Saleem, Mahira Pathan, Emaan Shahzad, Salam Dhou, Fadi Aloul

“…The proposed model is computationally efficient and easy to deploy, which ensures a fast, sustainable and low power-consuming intrusion detection system at the cutting edge.…”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…In outdoor field experiments conducted under cloudy, low-light, and artificial lighting conditions, the model achieved localization errors of 2.43 mm (X-axis), 3.70 mm (Y-axis), and 1.28 mm (Z-axis), representing reductions of 19.27 %, 12.67 %, and 23.05 %, respectively. …”
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Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm by Mingyu GAO, Jiusheng BAO, Yan YIN, Deping HU, Kekun ZHANG, Chenzhong ZHU, Maosen WANG, Kai WANG

“…In order to solve the problem of low driving efficiency and poor path quality caused by excessive detour during path planning, a “3D-like” path planning method based on optimized ant colony algorithm was proposed, and its effectiveness was verified by simulation and experiment. …”
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MVTC-Sec: Lightweight Timestamp Correlation for Securing RPL Against DIO Replay Attacks by Tahar Guerbouz, Akram Zine Eddine Boukhamla, Djalila Belkebir, Sahraoui Dhelim

“…To address these issues, this paper proposes MVTC-Sec, a Mathematically Validated Timestamp Correlation method that detects replay-based DIO attacks by analyzing deviations from the expected Trickle algorithm timing. …”
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A Novel Spectrum Sensing Method for Multiple Unknown Signal Sources Using Frequency Domain Energy Detection and DBSCAN by Rui Gao, Guanghui Yan, Ruiting Niu, Wenwen Chang, Tianfeng Yan, Chunyang Tang

“…While the energy detection (ED) method is widely used for spectrum sensing, it struggles with noise uncertainty (NU) and in low signal-to-noise ratio (SNR) environments. …”
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ClipQ: Clipping Optimization for the Post-Training Quantization of Convolutional Neural Network by Yiming Chen, Hui Zhang, Chen Zhang, Yi Liu

“…In addition, the particle swarm algorithm is applied in weight clipping to adjust the search step size and direction adaptively. …”
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Certificateless Batch Authentication Scheme and Intrusion Detection Model Based on the Mobile Edge Computing Technology NDN-IoT Environment by Jianzhao Sun

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Machine Vision Applications for Welfare Monitoring in Aquaculture: Challenges and Opportunities by Amy Fitzgerald, Christos C. Ioannou, Sofia Consuegra, Andrew Dowsey, Carlos Garcia de Leaniz

“…Object detection algorithms, such as YOLO, have been the approach of choice for most MV applications in aquaculture, but our review has identified an increasing number of alternatives that can help circumvent some of the challenges posed by high densities and poor lighting typical of commercial farms. …”
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Sensitive and specific peak detection for SELDI-TOF mass spectrometry using a wavelet/neural-network based approach. by Vincent A Emanuele, Gitika Panicker, Brian M Gurbaxani, Jin-Mann S Lin, Elizabeth R Unger

“…In this work, we study the preprocessing of SELDI in detail and introduce improvements. While many algorithms, including the vendor supplied software, can identify peak clusters of specific mass (or m/z) in groups of spectra with high specificity and low false discover rate (FDR), the algorithms tend to underperform estimating the exact prevalence and intensity of peaks in those clusters. …”
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ST-YOLO: A defect detection method for photovoltaic modules based on infrared thermal imaging and machine vision technology. by Hanfei Xie, Baoxi Yuan, Chengyu Hu, Yujie Gao, Feng Wang, Chunlan Wang, Yuqian Wang, Peng Chu

“…To address the shortcomings of existing photovoltaic defect detection technologies, such as high labor costs, large workloads, high sensor failure rates, low reliability, high false alarm rates, high network demands, and slow detection speeds of traditional algorithms, we propose an algorithm named ST-YOLO specifically for photovoltaic module defect detection. …”
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Enhancing Cloud Detection in Polar Regions Using Combined Spectral and Textural Features for Landsat 8/9 OLI Imagery by Xinran Shen, Teng Li, Chong Liu, Shaoyin Wang, Lei Zheng, Qi Liang, Xiao Cheng, Jiaqi Yao

“…However, cloud cover in optical remote sensing images can diminish the data integrity for certain snow/ice applications. Existing cloud detection algorithms are primarily designed for mid and low latitude images, which poses significant challenges in polar regions due to the similar spectral characteristics of clouds and snow/ice surface. …”
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Enhanced Infrared Defect Detection for UAVs Using Wavelet-Based Image Processing and Channel Attention-Integrated SSD Model by Jining Zhao, RuiZhi Zhang, Shaogong Chen, Yanbo Duan, Zhiyuan Wang, Qingchen Li

“…In this paper, we develop a defect target detection algorithm based on image processing and feature matching to address background noise in the detection of defects in infrared images of Unmanned Aerial Vehicle (UAVs), as well as to improve real-time monitoring capabilities. …”
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An Optimization Method for PCB Surface Defect Detection Model Based on Measurement of Defect Characteristics and Backbone Network Feature Information by Huixiang Liu, Xin Zhao, Qiong Liu, Wenbai Chen

“…Printed Circuit Boards (PCBs) are essential components in electronic devices, making defect detection crucial. PCB surface defects are diverse, complex, low in feature resolution, and often resemble the background, leading to detection challenges. …”
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Experimental study and techno-economic evaluation of an active fault detection kit in the prospect of future zero energy building installations by Christos Pechlivanis, Nick Rigogiannis, Andreas Tichalas, Faidra Kotarela, Nick Papanikolaou

“…Its operation is based on harmonic voltage injection, in series with the electrical installation, through a low-power H-bridge inverter and a current transformer, along with the corresponding harmonic current measurement, to estimate the impedance and effectively detect faulty conditions; the fast and robust Goertzel algorithm is utilized. …”
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