Measurement-induced entanglement entropy of gravitational wave detections by Preston Jones, Quentin G. Bailey, Andri Gretarsson, Edward Poon

“…Coincident multiple detector operations make it possible to consider the bipartite measurement-induced entanglement, in the detection process, as a signature of non-classicality. …”
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Detection and Classification of Emotional State Based on Speech Signal by Hiba Younis, Mrewan Mustafa, Rahma Raad

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Detection and Defense: Student-Teacher Network for Adversarial Robustness by Kyoungchan Park, Pilsung Kang

“…In this paper, we propose a novel defense method based on the student-teacher framework that can minimize the classification performance degradation for NEs by detecting AEs and then applying the defense process only to AEs. …”
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HEAVY METALS DETECTION IN ATMOSPHERIC FALLOUT AND AMBIANT AIR by YOUNES KHDAYCHI, LAILA IDRISSI

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Development of an SPRi Immune Method for the Quantitative Detection of Osteopontin by Anna Sankiewicz, Beata Żelazowska-Rutkowska, Tomasz Guszcz, Ewa Gorodkiewicz

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Cost-effective annotation of fisheye images for object detection by K. Zhang, A. Elalailyi, L. Perfetti, F. Fassi

“…It also seeks a way to prove that the annotation can be converted to fisheye images, resulted into a pre-process, which will facilitate the data preparation process. …”
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Parameter Adaptive LCD Screen Defect Detection Framework by LIU Wang, SHAO Huili, HE Yongjun, XIE Yining, CHEN Deyun

“…It is necessary to detect defects in the production process of LCD screens for quality improvements Manual detection brings a heavy workload and low accuracy Therefore, an efficient and accurate automatic detection method is urgently needed To this end, this paper proposes a new defect detection framework, which mainly includes screen area extraction, preprocessing, threshold segmentation and defect selection By adaptive adjustment of parameters, the detection method can adapt to various complex situations In order to eliminate the influence of illumination changes, the defect region is segmented by automatic parameter adjustment in the threshold segmentation First, the maximum grayscale value of the image is calculated, and then the fixed parameters and the coefficient of the defect image are determined according to the nodefect image, and finally the maximum value which was selected as the minimum threshold of the threshold segmentation from the fixed parameters and the product of the maximum grayscale value and the coefficient In addition, in order to solve the problem that the brightness difference of the images captured by lowresolution cameras is too small to detect defects in the saturation condition, selfadaptive adjustment of exposure parameters was used to collect images to process different parts of images with large difference in light and shade Experiments show that the method can achieve high performance and efficiency in detecting defects such as points, lines, Mura, saturation…”
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Center-Guided Network with Dynamic Attention for Transmission Tower Detection by Xiaobin Li, Zhuwei Liang, Jingbin Yang, Chuanlong Lyu, Yuge Xu

“…In addition, a two-stage detection head is proposed to employ a two-stage detection process to perform more accurate detection. …”
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Identification of orthohantaviruses detected for the first time in the Republic of Belarus by Pavel A. Semizhon, Elena P. Scheslenok, Nikita A. Dubkov, Elizaveta A. Sukhotskaya, Kristina A. Stolbunova, Igor V. Popov, Ilia V. Popov, Alexander Y. Alekseev, Emmanuel Kabwe, Yuri N. Davidyuk

“…Comparative and phylogenetic analysis was carried out using the MegAlign programs from the Lasergene package (DNASTAR, USA) and MEGA 11. …”
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CLEAN Technique to Classify and Detect Objects in Subsurface Imaging by E. Karpat

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Explainable handcrafted features for mitotic event detection and classification by Panason Manorost, Thomas Deckers, Veerle Bloemen, Jean Marie Aerts

“…These unwanted noise elements and artifacts can cause false positive detections and lead to low precision in detecting proliferation processes. …”
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Method of detecting network anomaly on multi-time-scale by WANG Feng-yu1, YUN Xiao-chun1, CAO Zhen-zhong4

“…To detect anomaly timely and precisely in high-speed network,an algorithm,named DA-MTS（detecting anomaly on multi-time-scale synchronously）,was proposed.Firstly,pre-process the time series of traffic with non-decimated Haar wavelet transform to produce detail signals,which approximately follow Gaussian white noise.Then detect anomaly based on "3σ" principal of normal distribution.Analysis and experiments reveal that this algorithm can detect anomaly on several time-scales recursively without delay,so it can detect anomaly precisely and timely.…”
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Deviance detection and regularity sensitivity in dissociated neuronal cultures by Zhuo Zhang, Amit Yaron, Dai Akita, Tomoyo Isoguchi Shiramatsu, Zenas C. Chao, Hirokazu Takahashi, Hirokazu Takahashi

“…Crucially, we also showed sensitivity to the statistical regularity of stimuli, a phenomenon previously observed only in intact brains: the MMRs in a predictable, periodic sequence were smaller than those in a commonly used sequence in which the appearance of the deviant stimulus was random and unpredictable.DiscussionThese results challenge the traditional view that a hierarchically structured neural network is required to process complex temporal patterns, suggesting instead that deviant detection and regularity sensitivity are inherent properties arising from the primitive neural network. …”
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Study on user behavior profiling in insider threat detection by Yuanbo GUO, Chunhui LIU, Jing KONG, Yifeng WANG

“…Behavior profiling technic using no-labeled historical data to build normal behavior model is an effective way to detect insider attackers. The state-of-the-art labeled profile methods extract features artificially and process data by simple statistical methods, whose incomplete behavior model lacks details. …”
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Approach to detecting SQL injection behaviors in network environment by Yu-fei ZHAO, Gang XIONG, Long-tao HE, Zhou-jun LI

“…SQL injection attack is one of the main threats that many Web applications faced with. The traditional detection method depended on the clients or servers. …”
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GHSOM intrusion detection based on Dempster-Shafer theory by Jie SU, Wei-wei DONG, Xuan XU, Shuai LIU, Li-peng XIE

“…On the basis of incremental GHSOM,the GHSOM neural network intrusion detection based on the theory of evidence reasoning method was put forward.It can deal with the uncertainty caused by randomness and fuzziness,as well as can constantly narrowing assumptions set by accumulate the evidence,effectively control dynamic growth of network and keep a good accuracy in noise environment.Experiments show that GHSOM intrusion detection method based on the Dempster Shafer theory realized the dynamic control for the scale of expended subnet during the process of detection.It has the better detection accuracy in the noise environment and improves the adaptability and extensibility of incremental GHSOM neural network intrusion detection method when the scale of network is expanded.…”
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Concept Drift Detection in Dynamic Probabilistic Relational Models by Nils Finke, Tanya Braun, Marcel Gehrke, Ralf Möller

“…We propose an approach to account for non-stationary processes w.r.t. to changing probability distributions over time, an effect known as concept drift. …”
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Grasp Detection under Occlusions Using SIFT Features by Zhaojun Ye, Yi Guo, Chengguang Wang, Haohui Huang, Genke Yang

“…There are two key steps for the proposed method in the process of grasping occluded object: generating template information and grasp detection using the matching algorithm. …”
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Method for Detecting Disorder of a Nonlinear Dynamic Plant by Xuechun Wang, Vladimir Eliseev

“…Also, CCF-AE has more advantages in detecting disorder of complex nonlinear processes.…”
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Policy-focused Stance Detection in Parliamentary Debate Speeches by Gavin Abercrombie, Riza Batista-Navarro

“… Legislative debate transcripts provide citizens with information about the activities of their elected representatives, but are difficult for people to process. We propose the novel task of policy-focused stance detection, in which both the policy proposals under debate and the position of the speakers towards those proposals are identified. …”
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