Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits by Yun Zhao, Yang Li, Xing Xu

“…We also introduced a non-maximal suppression algorithm, Cluster-NMF, which accelerates inference speed through matrix parallel computation and merges multiple high-quality target detection frames to generate an optimal detection frame, enhancing the efficiency of blueberry canopy fruit detection without compromising inference speed.…”
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Fast real-time detection and counting of thrips in greenhouses with multi-level feature attention and fusion by Zhangzhang He, Xinyue Chen, Ying Gao, Yu Zhang, Yuheng Guo, Tong Zhai, Xiaochen Wei, Huan Li, Haipeng Zhu, Yongkun Fu, Zhiliang Zhang, Zhiliang Zhang

“…Compared to existing methods, TCD-Net achieves higher thrips counting and detection accuracy with lower computational complexity. …”
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Adaptive Fuzzy C-Means with logit boost distributed clustering for cancer detection with protein sequences by K. Thenmozhi, M. Pyingkodi, V. S. Prakash, Kripa Josten, S. Manju Priya, J. Vennila

“…Abstract The Adaptive Fuzzy C-Means with Logit Boost Distributed Clustering (AFC-LBDC) technique is introduced to enhance cancer detection promptly. The various conventional techniques often struggle to improve cancer detection due to their high complexity effectively. …”
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State-of-the-Art Methodologies for Self-Fault Detection, Diagnosis and Evaluation (FDDE) in Residential Heat Pumps by Francesco Pelella, Adelso Flaviano Passarelli, Belén Llopis-Mengual, Luca Viscito, Emilio Navarro-Peris, Alfonso William Mauro

“…The complexity and added value of these tools grow as they progress from simple fault detection to quantitative fault evaluation, enabling more accurate and timely maintenance strategies. …”
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Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques by Shoayee Dlaim Alotaibi, Abeer A. K. Alharbi

“…Next, the EADCD-TIPAIT technique performs a binary greylag goose optimization (BGGO)-based feature selection approach to efficiently identify relevant features that distinguish between normal and dementia-affected brain regions. …”
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Enhanced BDS four-frequency cycle slip detection and repair using fuzzy clustering analysis by Jinfeng Yuan, Xiaoning Su, Yuzhao Li

“…It is worth noting that during the repair process, the coefficients of the combined observation values are integers, preserving the integer cycle characteristic of the observation values, which allows cycle slips to be fixed directly, eliminating the need for complex searching procedures. …”
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Intrusion detection system based on machine learning using least square support vector machine by Pratik Waghmode, Manideep Kanumuri, Hosam El-Ocla, Tanner Boyle

“…Unauthorized access or attack can be avoided in critical systems using a comprehensive approach via an effective intrusion detection system (IDS). Traditional intrusion detection techniques are no longer accurate and effective enough to handle the demands of the big data age. …”
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A comparative analysis of fault detection and process diagnosis methods based on a signal processing paradigm by Dorel Aiordăchioaie

“…The results of the computer-based experiments show acceptable performance for all methods for the test case of bearings but the potential to detect more complex faults and change detection in the behavior of the machines, in general. …”
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Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies by Jianxian Wang, Hazlie Mokhlis, Nurulafiqah Nadzirah Mansor, Hazlee Azil Illias, Agileswari K. Ramasamy, Xingyu Wu, Siqi Wang

“…However, with nations worldwide actively pursuing carbon neutrality and emission peak goals, sustainable energy sources such as solar and wind are increasingly penetrating distribution networks, posing significant challenges to conventional fault detection, classification, and localization techniques due to bidirectional power flows, dynamic fault currents, and rising network complexity. …”
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New Methods for Waterfowl and Habitat Survey Using AI and Drone Imagery by Zhenduo Zhai, Zhiguang Liu, Yang Zhang, Andrew Zhao, Yi Shang

“…Existing methods for waterfowl monitoring face critical challenges such as low accuracy in identifying overlapping image regions and limited segmentation accuracy in complex habitats. To address these issues, this paper presents an end-to-end system and several new methods for efficiently and accurately identifying waterfowl populations in their natural habitats using AI and drone imagery. …”
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A Hybrid Approach for Reachability Analysis of Complex Software Systems Using Fuzzy Adaptive Particle Swarm Optimization Algorithm and Rule Composition by Nahid Salimi, Seyfollah Soleimani, Vahid Rafe, Davood Khodadad

“…Experimental results demonstrate that proposed hybrid algorithm reduced verification time by up to 49.86% compared to Particle Swarm Optimization and 65.17% compared to Genetic Algorithms in reachability analysis of complex models. Furthermore, it explored 32.7% fewer states on average than the hybrid method based on Particle Swarm Optimization and Gravitational Search Algorithms, and 57.4% fewer states compared to Genetic Algorithms, indicating improved search efficiency. …”
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Real-Time Object Detection and Distance Measurement Enhanced with Semantic 3D Depth Sensing Using Camera–LiDAR Fusion by Ahmet Serhat Yildiz, Hongying Meng, Mohammad Rafiq Swash

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Multi-frequency EEG and multi-functional connectivity graph convolutional network based detection method of patients with Alzheimer’s disease by Yujian Liu, Libing An, Haiqiang Yang, Shuzhi Sam Ge

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P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…Traditional algorithms often face challenges in achieving high detection accuracy and efficiency when addressing the complex task of detecting densely distributed small objects. …”
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Performance Analysis of Maximum Likelihood Detection in Cooperative DF MIMO Systems with One-Bit ADCs by Tae-Kyoung Kim

“…Although joint maximum likelihood detection can efficiently mitigate error propagation by leveraging probabilistic information from a source-to-relay link, its computational complexity is impractical. …”
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Lightweight multidimensional feature enhancement algorithm LPS-YOLO for UAV remote sensing target detection by Yong Lu, Minghao Sun

“…LPS-YOLO introduces the SKAPP module for better feature fusion and incorporates the E-BiFPN and OFTP structures to efficiently preserve and transfer backbone information. …”
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Prioritizing image processing and big data analytics factors for software development using DEMATEL-choquet method in bipolar complex fuzzy context by Ruimin Ma

“…The causal effects indicate that feature extraction, automation and efficiency, as well as object detection, are critical causal factors, whereas image enhancement, security, and segmentation are dependent effects. …”
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Robust Target Detection and Estimation for Airborne STAP Radar With Arbitrary Array Errors and Target Uncertainty by Jianxin Wu, Yang Zhao, Changxian Li, Peng Shen

“…Finally, target angle estimation using subspace coefficients, which implements the ML estimator in a reduced-dimensional version, is presented to reduce the computational complexity of the ML estimator. …”
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YOLOv7scb: A Small-Target Object Detection Method for Fire Smoke Inspection by Dan Shao, Yu Liu, Guoxing Liu, Ning Wang, Pu Chen, Jiaxun Yu, Guangmin Liang

“…Additionally, a weighted bidirectional feature pyramid network (BiFPN) is integrated into the feature-extraction network to merge features across scales efficiently without increasing the model’s complexity. …”
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Transforming Retinal Photographs to Entropy Images in Deep Learning to Improve Automated Detection for Diabetic Retinopathy by Gen-Min Lin, Mei-Juan Chen, Chia-Hung Yeh, Yu-Yang Lin, Heng-Yu Kuo, Min-Hui Lin, Ming-Chin Chen, Shinfeng D. Lin, Ying Gao, Anran Ran, Carol Y. Cheung

“…Entropy images, representing the complexity of original fundus photographs, may strengthen the contrast between diabetic retinopathy (DR) lesions and unaffected areas. …”
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