A Strawberry Ripeness Detection Method Based on Improved YOLOv8 by Yawei Yue, Shengbo Xu, Huanhuan Wu

“…An enhanced YOLOv8-based network was developed to accurately and efficiently detect the ripeness of strawberries in complex environments. …”
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Pedestrian dynamics modeling and social force analysis based on object detection by Fangyan Yang, Rong Liu, Daoyu Zhu

“…IGVIF formulates pedestrian detection as a probabilistic inference problem, leveraging principles from information geometry to efficiently explore high-dimensional parameter spaces. …”
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Fast and Accurate Detection of Forty Types of Fruits and Vegetables: Dataset and Method by Xiaosheng Bu, Yongfeng Wu, Hongtai Lv, Youling Yu

“…However, existing detection methods typically focus on identifying a single type of fruit or vegetable and are not equipped to handle complex and diverse environments. …”
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Massive MIMO signal detection based on approximate message passing algorithm by Chuang QIN, Ziwei ZHENG, Daping LOU, Xianzu FU

“…Massive multiple-input multiple-output(MIMO)brings huge improvements in energy efficiency and reduces emission power by using a large number of antennas,which is known as a key technology in the fifth generation (5G)mobile communication.With the increasing number of antennas,the complexity of signal detection is increasing at the same time.According to the research status of massive MIMO signal detection,approximate message passing algorithm was proposed.The complexity of AMP was compared to some iteration algorithm like Richarson algorithm and Neumann series approximation algorithm.The results indicate that the proposed algorithm can use less iteration to achieve almost the same performance of MMSE algorithm.…”
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SWMD-YOLO: A Lightweight Model for Tomato Detection in Greenhouse Environments by Quan Wang, Ye Hua, Qiongdan Lou, Xi Kan

“…The accurate detection of occluded tomatoes in complex greenhouse environments remains challenging due to the limited feature representation ability and high computational costs of existing models. …”
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Improved FastICA algorithm for data optimization processing in intrusion detection by Ye DU, dan ZHANGYa, hong LIMei, wei ZHANGDa

“…The algorithm was introduced concretely, meanwhile the time complexity was analyzed in detail. The experiment shows that the method has the advantages of less times of iteration and fast speed of convergence, which can effectively decrease the losses of data and increase the efficiency of data optimization in in ion detection.…”
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A low-complexity M-shaped reconfigurable intelligent meta-surface for mitigating pathloss in wireless systems by Maira Khafagy, Sherief Fathi, Ahmed Magdy

“…This study presents a novel Low-Complexity M-shaped Reconfigurable Intelligent Metasurface (LCM-RIM) designed to mitigate path loss in indoor environments. …”
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The acoustic change complex as a diagnostic tool for cochlear dead regions evaluated in normally hearing adults by Anna Schelenz, Emanuele Perugia, Lin Wu, Ewa Skrodzka, Karolina Kluk

“…We found that the bootstrap method was most efficient at detecting ACC and was two times faster to administer than the commonly used British Society of Audiology method. …”
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LiteTom-RTDETR: A Lightweight Real-Time Tomato Detection System for Plant Factories by Wenshuai Liu, Qingzheng Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qiang Liu, Yuxiang Tian

“…The proposed LiteTom-RTDETR model was shown to balance high tomato identification accuracy (88.2%) with an excellent real-time inference speed (52.2 frames per second) and computational efficiency (36.3 GFLOPs). Notably, the average detection accuracy of LiteTom-RTDETR was 0.6% higher, its detection speed was 15.5% faster, and its computational load and model size were 36.2% and 31.6% smaller, respectively, than those of the original RTDETR model. …”
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Detecting DDoS attack based on compensation non-parameter CUSUM algorithm by YAN Fen1~3, CHEN Yi-qun3, HUANG Hao1, YIN Xin-chun3

“…t,calculated the ratio of the number of unacknowledged segments and the number of all segments.Then,the statistical sequence based on time came into being.After that,an improved non-parameter recursive CUSUM algorithm was used to detect attack effi-ciently on line.In this procedure,the suspicious packets were also recorded.Experiments prove that this algorithm is fast and efficient.It has low false-positive rate and could adapt to more complex network environments.In addition,it is helpful to attack analysis and tracing.…”
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Optimal resource allocation for two-stage connectionless access with collision detection by Xin JIAN, Fang WANG, Jian SONG, Shu FU, Xiaoheng TAN, Xiaoping ZENG

“…Connectionless access allows massive machine type communication (mMTC) devices to transmit small packets without establishment of radio bearers,significantly reducing device power consumption and control signaling overhead.Two-stage connectionless access (TSCLA) improves throughput and resource efficiency by optimally allocating resources between scheduling request (SR) phase and data transmission phase,which can be used for bigger packets and high traffic load.Based on this,a comprehensive theoretical analysis of one kind of TSCLA with collision detection was conducted to investigate its performance limit and devise its optimal resource allocation scheme.In addition,to avoid the complexity of user number estimation,a dynamic resource allocation algorithm with feedback control was proposed.Numerical results are provided to validate the effectiveness of aforementioned theoretical results and show that comparing with the genie aided algorithm known exactly the number of users,the performance loss of the proposed algorithm is within 4%.These works together provide good references for appropriate resource dimensioning for mMTC related protocols.…”
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Lightweight RT-DETR with Attentional Up-Downsampling Pyramid Network by Nan Li, Xiao Han, Xingguo Song, Xu Fang, Mengming Wu, Qiulin Yu

“…To address this, we propose an improved RT-DETR R18 model tailored for companion robots. This lightweight, efficient design integrates YOLOv9’s ADown module, the RepNCSPELAN4 module, and custom attention-based AdaptiveGateUpsample and AdaptiveGateDownsample modules for enhanced multi-scale feature fusion, reducing weight and complexity while optimizing real-time detection. …”
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A Small Target Pedestrian Detection Model Based on Autonomous Driving by Yang Zhang, Shuaifeng Zhang, Dongrong Xin, Dewang Chen

“…Finally, a cascaded autofocus query module is proposed to increase the inference speed of the feature pyramid network through focusing and querying, thus improving the performance and efficiency of small-target pedestrian detection. The experimental results show that the proposed model achieves better detection results than previous models.…”
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Driver Distraction Detection in Extreme Conditions Using Kolmogorov–Arnold Networks by János Hollósi, Gábor Kovács, Mykola Sysyn, Dmytro Kurhan, Szabolcs Fischer, Viktor Nagy

“…The results suggest that KANs can enhance driver distraction detection under challenging conditions, with improved resilience against adversarial attacks, particularly in low-complexity networks.…”
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Deep learning-based anomaly detection for precision field crop protection by Cheng Wei, Yifeng Shan, MengZhe Zhen

“…IntroductionPrecision agriculture relies on advanced technologies to optimize crop protection and resource utilization, ensuring sustainable and efficient farming practices. Anomaly detection plays a critical role in identifying and addressing irregularities, such as pest outbreaks, disease spread, or nutrient deficiencies, that can negatively impact yield. …”
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Moving Vehicles Detection and Tracking on Highways and Transportation System for Smart Cities by Manoj Kumar, Susmita Ray, Dileep Kumar Yadav

“…In this paper, various approaches related to moving vehicle detection for the transportation system especially for highways are considered. …”
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Frequency-informed transformer for real-time water pipeline leak detection by Fengnian Liu, Ding Wang, Junya Tang, Lei Wang

“…Abstract Water pipeline leaks pose significant risks to urban infrastructure, leading to water wastage and potential structural damage. Existing leak detection methods often face challenges, such as heavily relying on the manual selection of frequency bands or complex feature extraction, which can be both labour-intensive and less effective. …”
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Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…To address these issues, we introduce a novel one-stage network that enables real-time detection of insulator faults on mobile devices. We designed a new module that optimises the computational complexity of networks and fused the module with the attention mechanism SimAM to solve the problem of low efficiency in detecting flashover faults. …”
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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

“… In recent years, Deep Neural Networks (DNN) have demonstrated remarkable success in various domains, including Intrusion Detection Systems (IDS). The ability of DNN to learn complex patterns from large datasets has significantly improved IDS performance, leading to more accurate and efficient threat detection. …”
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A Sparse Pooling Adversarial Learning Framework for Anomaly Event Detection by ZHANG, M., HU, H., LI, Z.

“…However, due to factors of complex background, large changes in scale, and the randomness of abnormal events, causing abnormal event detection poses significant challenges. …”
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