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AI Content Detector Détecteur de contenu basé sur l'IA : détecte GPT-4, BARD, Copilot et Claude. Détecte le contenu écrit par IA à l'aide des principaux modèles de génération d'IA tels que GPT4, BARD, Claude et Copilot. Le détecteur de contenu basé sur l'IA est...
Method of body X-ray scanning, an apparatus for its implementation and a radiation detector (3 version) thereof The invention relates to the field of engineering physics in particular to the technique for detecting X-radiation, and it may be used for photometry, dosimetry as well as for measur...
The BNL one-sided 3D detectors were compared to various 3D detector structures developed by other institutes. The field profiles for all types of dual-type column 3D detectors are similar with just some minor differences on both surfaces (front and back). The BNL single-type column one-sided ...
When the count was at 320 (now almost 500), more than half of the mill papers came from the Shandong province, almost a fifth from Jilin and one tenth from Henan. This message was sent to Tiger BB8 by such a Chinese paper mill customer: ...
In the remainder of the paper, other survey papers on testing ML systems will be mentioned, but are omitted from this discussion, due to the fact that they will be discussed later on in the paper. Batarseh [7] defines a new AI assurance definition and maps different AI subarea (for ...
binaries compiled from the same source code may vary considerably, which becomes the major obstacle for these works to obtain robust features. In this paper, we propose a solution, named UPPC (Unleashing the Power of Pseudo-code), which leverages the pseudo-code of binary function as input, ...
The position estimation in the detector’s monolithic and DOI direction was based on the machine learning technique gradient tree boosting (GTB) [2, 3]. We have recently demonstrated a high-throughput implementation of GTB to demonstrate the computational feasibility for large-scale systems [4]. ...
Several comparative experiments have also validated the effectiveness of this paper’s improvements to the YOLOv4 algorithm and the superiority of these structures. With the effective integration of these components, the algorithm shows high accuracy and real-time performance. ...
In this paper, we divide MF-based malicious code detection methods into two types based on different technical bases: method based on the characteristics of operating system and memory pages (OS Characteristics Based), and detection method combining artificial intelligence (AI Based). Figure 2 ...