An insulator target detection algorithm based on improved YOLOv5 by Bing Zeng, Zhihao Zhou, Yu Zhou, Dilin He, Zhanpeng Liao, Zihan Jin, Yulu Zhou, Kexin Yi, Yunmin Xie, Wenhua Zhang

“…Abstract Drone inspections are widely utilized in the detection of insulators in power lines. To address issues with traditional object detection algorithms, such as large parameter counts, low detection accuracy, and high miss rates, this paper proposes an insulator detection algorithm based on an improved YOLOv5 model. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Abstract The DEtection TRansformer (DETR) and the YOLO series have been at the forefront of advancements in object detection. …”
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Field Obstacle Detection and Location Method Based on Binocular Vision by Yuanyuan Zhang, Kunpeng Tian, Jicheng Huang, Zhenlong Wang, Bin Zhang, Qing Xie

“…Additionally, the use of a Poly Kernel Inception (PKI) Block reduces model size while improving obstacle detection across various scales. …”
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Improved Field Obstacle Detection Algorithm Based on YOLOv8 by Xinying Zhou, Wenming Chen, Xinhua Wei

“…First, to adapt to different tasks and complex environments in the field, improve the sensitivity of the detector to various target sizes and positions, and enhance detection accuracy, the CBAM (Convolutional Block Attention Module) was integrated into the backbone layer of the benchmark model. …”
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Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…However, challenges such as overlapping spikes in unmanned aerial vehicle (UAV) images and the computational requirements for high-resolution image analysis hinder real-time detection capabilities. To address these issues, this study proposes an improved lightweight YOLOv5 model for highland barley spike detection. …”
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THANTD: Triplet Hybrid Attention Network for Hyperspectral Target Detection by Ju Liu, Haoqian Wang, Xiangai Cheng, Zhongyang Xing, Zhongjie Xu

“…Hyperspectral images (HSIs), characterized by their rich spatial–spectral information, have been widely utilized in hyperspectral target detection (HTD), a key area within hyperspectral remote sensing information processing. …”
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Optimized Microfluidic Biosensor for Sensitive C-Reactive Protein Detection by Amirmahdi Tavakolidakhrabadi, Matt Stark, Alexander Küenzi, Sandro Carrara, Cédric Bessire

“…This approach minimizes the non-specific binding of conjugated antibodies to unwanted areas of the NC pad, eliminating the need to block those areas, which enhances the sensitivity of detection. …”
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Aortic Aneurysm Inflammatory Cell Detection with Deep Learning methods by Kristóf-Gergö Nagy, Csaba Szferle, Attila Fintha

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Optimizing Monkeypox Lesions Detection With a Lightweight Hybrid Model by Mehdhar S. A. M. Al-Gaashani, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Abduljabbar S. Ba Mahel, Ahmed Aziz, Mashael M. Khayyat, Ammar Muthanna

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Field Measurement and Mechanical Analysis of Height of the Water Flowing Fracture Zone in Short-Wall Block Backfill Mining beneath the Aquifer: A Case Study in China by Yun Zhang, Shenggen Cao, Tong Wan, Jijun Wang

“…Short-wall block filling mining (SBBM) technology has become an effective way to recover coal resources beneath the aquifer, which are unsuitable, or cannot be used by long-wall mining, such as corner coal pillars, industrial square pillars, and irregular coal blocks as well as the coal beneath buildings, railways, and water bodies. …”
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BFER-Net: Babies Facial Expression Recognition Model Using ResNet12 Enabled Few-Shot Embedding Adaptation and Convolutional Block Attention Modules by Sumiya Arafin, Adnan Ferdous Ashrafi, Md. Golam Rabiul Alam, Ashis Talukder

“…Here, we have deployed the feature extraction process. A Convolutional Block Attention Module (CBAM) was integrated into the Modified ResNet12 architecture. …”
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Allergen-Specific IgG Antibodies Purified from Mite-Allergic Patients Sera Block the IgE Recognition of Dermatophagoides pteronyssinus Antigens: An In Vitro Study by Isabella Lima Siman, Lais Martins de Aquino, Leandro Hideki Ynoue, Juliana Silva Miranda, Ana Claudia Arantes Marquez Pajuaba, Jair Pereira Cunha-Júnior, Deise Aparecida Oliveira Silva, Ernesto Akio Taketomi

“…One of the purposes of specific immunotherapy (SIT) is to modulate humoral immune response against allergens with significant increases in allergen-specific IgG levels, commonly associated with blocking activity. The present study investigated in vitro blocking activity of allergen-specific IgG antibodies on IgE reactivity to Dermatophagoides pteronyssinus (Dpt) in sera from atopic patients. …”
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Preoperative Analgesia Efficacy of Liposomal Bupivacaine Following Pericapsular Nerve Group (PENG) Block in Patients with Hip Fracture: A Randomized Controlled Observer-Blinded Stu... by Haobin Peng, Jiajun Wen, Manli Chen, Zhengyuan Xia, Ying Jiang, Kaiqi Xie, Weitao Huang, Bangsheng Cui, Peixing Li, Yiwen Zhang, Xianping Wu

“…No significant inter-group differences were detected in other secondary outcomes. Conclusions For preoperative analgesia of hip fractures, LB single-injection PENG block had a similar analgesic intensity and safety as ropivacaine but provided a longer duration of analgesia, reaching 48 h and even extending beyond 60 h, which reduced opioid consumption and extended time to the first opioid. …”
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SFSCDNet: A Deep Learning Model With Spatial Flow-Based Semantic Change Detection From Bi-Temporal Satellite Images by K. S. Basavaraju, N. Sravya, Vibha Damodara Kevala, Shilpa Suresh, Shyam Lal

“…The Attention-Based Siamese Encoder, Cascaded Convolutional Attention Fusion Block, Cascaded Convolutional Attention Refinement Block and Differentiable Binarization layer helps in improving semantic change detection performance. …”
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Physical-social attributes integrated Sybil detection for Tor bridge distribution by Xin SHI, Yunfei GUO, Yawen WANG, Xiaoli SUN, Hao LIANG

“…As one of the most widely utilized censorship circumvention systems, Tor faces serious Sybil attacks in bridge distribution.Censors with rich network and human resources usually deploy a large number of Sybils, which disguise themselves as normal nodes to obtain bridges information and block them.In the process, due to the different identities, purposes and intentions of Sybils and normal nodes, individual or group behavior differences occur in network activities, called as node behavior characteristics.To handle the Sybil attacks threat, a Sybil detection mechanism integrating physical-social attributes was proposed based on the analysis of node behavior characteristics.The physical-social attributes evaluation methods were designed.The credit value of nodes objectively reflecting the operation status of bridges on the nodes and the suspicion index of nodes reflecting the blocking status of bridges, were utilized to evaluate the physical attributes of nodes.The social attributes of nodes were evaluated by the social similarity, which described the static attribute labels of nodes and their social trust characterizing the dynamic interaction behaviors of nodes.Furthermore, integrating the physical-social attributes, the credibility of nodes were defined as the possibility of the current node being a Sybil, which was exploited as a guidance on inferring the true identifies of nodes, so as to achieve accurate detection on Sybils.The detection performance of the proposed mechanism based on the constructed Tor network operation status simulator and the Microblog PCU dataset were simulated.The results show that the proposed mechanism can effectively improve the true positive rate on Sybils, and decrease the false positive rate.It also has stronger resistance on the deceptive behavior of censors, and still performs well in the absence of node social attributes.…”
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Function encoding based approach for App clone detection in cloud environment by Jia YANG, Cai FU, Lansheng HAN, Hongwei LU, Jingliang LIU

“…An efficient function-based encoding scheme in the cloud environment for detecting the cloned Apps was designed,called Pentagon.Firstly,a basic block feature extraction method was proposed.Secondly,a monotonic encoding algorithm for the App function was designed,which encoded the function based on the control flow graph structure and basic block attributes.Finally,a three-party libraries filtering method was proposed by using an efficient clustering algorithm based on the function feature.Experiments verified the effectiveness of the proposed scheme.The average search time is close to 79 ms,and the clone detection accuracy achieves 97.6%.…”
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A method for synthetic speech detection using local phase quantization by Jia XU, Zhihua JIAN, Honghui JIN, Man YANG

“…Due to the convenience of speech synthesis, synthesized disguised speech poses a great threat to the security of speaker verification systems.In order to further enhance the ability of detecting the camouflage to the speaker verification system, a method of synthetic speech detection was put forward using the information in spectral domain of the synthetic speech spectrogram.The method employed the local phase quantization (LPQ) algorithm to describe frequency domain information in the speech spectrogram.Firstly, the spectrogram was divided into several sub-blocks, and then the LPQ was performed on each sub-block.After the histogram statistical analysis, the LPQ feature vector was obtained and used as the input feature of the random forest classifier to realize the synthetic speech detection.The experimental results demonstrate that the proposed method further reduces tandem detection cost function (t-DCF) and has better generalization ability.…”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…The proposed architecture incorporates 40 convolutional layers, 4 pooling layers, 4 inverted bottleneck blocks, 4 bottleneck blocks, 5 fuzzy layers, and a fully connected layer designed to enhance accuracy and stability when analyzing remotely sensed data. …”
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Detection of latent brain states from spontaneous neural activity in the amygdala. by Alexa Aucoin, Kevin K Lin, Katalin M Gothard

“…Indeed, the spontaneous firing rates of neurons in the amygdala are different during blocks of gentle grooming touches delivered by a trusted social partner, and during blocks of non-social airflow stimuli delivered by a computer-controlled air valve. …”
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Detection of human activities using multi-layer convolutional neural network by Essam Abdellatef, Rasha M. Al-Makhlasawy, Wafaa A. Shalaby

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