IECAU-Net: A Wood Defects Image Segmentation Network Based on Improved Attention U-Net and Attention Mechanism by Yingda Dong, Chunguang He, Xiaoyang Xiang, Yuhan Cui, Yongkang Kang, Anning Ding, Huaqiong Duo, Ximing Wang

“…Due to the heavy workload, low efficiency, and low accuracy of manual inspection, traditional machine learning methods have strong specialization, complex methods, and high costs. …”
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Research on real-time monitoring method of mine personnel protective equipment with improved YOLOv8 by Lei ZHANG, Zhipeng SUN, Hongjing TAO, Shangkai HAO, Qianru YAN, Xiwei LI

“…Coal mine underground environment is more complex, video surveillance is susceptible to noise, light and dust and other factors interference, resulting in the existing target detection methods for mine personnel protective equipment there are low detection accuracy, poor real-time, model complexity and so on, proposed an improvement of YOLOv8 real-time monitoring of mine personnel protective equipment method, known as DBE-YOLO. …”
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Applications and Prospects of CRISPR/Cas9 Technology in the Breeding of Major Tropical Crops by Lixia Zhou, Xianhai Zeng, Yaodong Yang, Rui Li, Zhihao Zhao

“…However, the modern molecular breeding of these crops is severely hampered by their biological characteristics and genetic complexity. Issues such as polyploidy, heterozygosity, vegetative propagation, long juvenile periods, and large plant sizes result in time consuming, low efficiency, and slow progress in conventional breeding of the major tropical crops. …”
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Design and Implementation of an Intelligent Pest Status Monitoring System for Farmland by Xinyu Yuan, Zeshen He, Caojun Huang

“…For overlapping pest detection, EfficientNetv2-S replaces the YOLOv5s backbone and is combined with an Adaptive Feature Pyramid Network (AFPN), achieving 95.72% detection accuracy, 94.04% mAP, and 127 FPS. …”
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Gait Recognition With Wearable Sensors Using Modified Residual Block-Based Lightweight CNN by Md. Al Mehedi Hasan, Fuad Al Abir, Md. Al Siam, Jungpil Shin

“…However, most recent studies have focused on improving gait detection accuracy while neglecting model complexity in the deep learning domain, making them unsuitable for low-power wearable devices. …”
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Multi-Stage Neural Network-Based Ensemble Learning Approach for Wheat Leaf Disease Classification by Samia Nawaz Yousafzai, Inzamam Mashood Nasir, Sara Tehsin, Dania Saleem Malik, Ismail Keshta, Norma Latif Fitriyani, Yeonghyeon Gu, Muhammad Syafrudin

“…The various stages in the EL approach employ a multi-level framework to enhance feature extraction and capture complex data patterns. This improves the model’s emphasis on diseases while reducing the influence of complex backgrounds on disease identification. …”
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Factors and applications of carbon dioxide huff-and-puff technology in small toothbrush-shaped oil reservoirs by Jinyong Li, Hongyu Gong, Qin Qin, Rui Wu

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ChipletQuake: On-Die Digital Impedance Sensing for Chiplet and Interposer Verification by Saleh Khalaj Monfared, Maryam Saadat Safa, Shahin Tajik

“…The increasing complexity and cost of manufacturing monolithic chips have driven the semiconductor industry toward chiplet-based designs, where smaller, modular chiplets are integrated onto a single interposer. …”
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Comprehensive empirical evaluation of feature extractors in computer vision by Murat ISIK

“…Each feature extractor was assessed based on its architectural design and complexity, focusing on how these factors influence computational efficiency and robustness under various transformations. …”
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Fractal Algorithm for Multiple-lens Analyses by F. Abe

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Automatic serving method of volleyball training robot based on improved YOLOv5 and improved Hough transform by Tao Sun, Xiaolong He, Jiajun Zhang

“…However, due to the characteristics of volleyball, such as small size, fast speed, and susceptibility to occlusion and noise interference in complex backgrounds, traditional object detection methods are hard to meet their real-time and accuracy requirements. …”
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Bridging technology and ecology: enhancing applicability of deep learning and UAV-based flower recognition by Marie Schnalke, Jonas Funk, Andreas Wagner, Andreas Wagner

“…Notably, EfficientDet demonstrated the lowest model complexity, making it a suitable choice for applications requiring a balance between efficiency and detection performance. …”
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Effortless Student Attendance: A Smart Human-Computer Interactive System Using Real Time Facial Recognition by Ahmad S. Lateef, Mohammed Y. Kamil

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A Review of UAV Path-Planning Algorithms and Obstacle Avoidance Methods for Remote Sensing Applications by Dipraj Debnath, Fernando Vanegas, Juan Sandino, Ahmad Faizul Hawary, Felipe Gonzalez

“…It further analyses obstacle detection and avoidance methods, as well as their capacity to adapt, optimise, and compute efficiently in different operational environments. …”
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Edge-YOLO: Lightweight Multi-Scale Feature Extraction for Industrial Surface Inspection by Wang Guiqiang, Chen Junbao, Li Chengzhang, Lu Shuo

“…The increasing complexity of industrial quality control necessitates advanced defect detection systems capable of identifying small-scale surface anomalies with high precision. …”
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Multi-Domain Feature Incorporation of Lightweight Convolutional Neural Networks and Handcrafted Features for Lung and Colon Cancer Diagnosis by Omneya Attallah

“…The system uses several light deep networks (EfficientNetB0, MobileNet, and ResNet-18), which feature fewer layers and parameters, unlike traditional systems that depend on a single, parameter-complex deep network. …”
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Advances in Catalyst Design for β-Lactone Formation via Ring-Expansion Carbonylation by Ali Hasnain, Vinothkumar Ganesan, Sungho Yoon

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Secure Biometric Identification Using Orca Predators Algorithm With Deep Learning: Retinal Iris Image Analysis by Louai A. Maghrabi, Mohammed Altwijri, Sami Saeed Binyamin, Fouad Shoie Alallah, Diaa Hamed, Mahmoud Ragab

“…Besides, the SBRIC-OPADL technique exploits the EfficientNet model for the extraction of feature vectors. …”
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Through the Citizen Scientists’ Eyes: Insights into Using Citizen Science with Machine Learning for Effective Identification of Unknown-Unknowns in Big Data by Kameswara Bharadwaj Mantha, Hayley Roberts, Lucy Fortson, Chris Lintott, Hugh Dickinson, William Keel, Ramanakumar Sankar, Coleman Krawczyk, Brooke Simmons, Mike Walmsley, Izzy Garland, Jason Shingirai Makechemu, Laura Trouille, Clifford Johnson

“…Volunteer-selected images with common astrophysical characteristics had higher consensus, while rarer or more complex ones had lower consensus. …”
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Pseudo-LiDAR With Two-Dimensional Instance for Monocular Three-Dimensional Object Tracking by Rui Gao, Junoh Kim, Phuong Minh Chu, Kyungeun Cho

“…This uncertainty poses additional challenges to object tracking as well, making performing stable multiple-object tracking on monocular 3D detection results more complex and difficult. To address these challenges in monocular 3D multiple-object detection and tracking, we propose the innovative framework pseudo-LiDAR-MOT, which accurately infers complete 3D bounding box information from 2D image sequences captured by a monocular camera and efficiently correlates and tracks moving objects in the temporal dimension. …”
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