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"content": "The main challenge of MESMERISE is to develop a new scanning technology improving the respect for intimacy and privacy rights as well as the efficiency and reliability. The first objective is to develop a high-resolution non-intrusive scanner able to automatically detect and identify both internal and external concealed prohibited or restricted commodities sought by customs such as drugs or explosives and to discern them from natural body tissues, food waste or benign materials. Mesmerise proposes two complementary technologies: ultra-low dose Multispectral X-ray transmission and Infrasonic interrogation. Both systems have the goals of improving privacy, convenience, sensitivity and reliability posing no risk for users, providing automatic identification or classification and assuring that no human operator needs to watch privacy-breaking images. www.h2020mesmerise.eu",
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"content": "Scenario 1: Scenario 2: Internally concealed commodities Externally concealed commodities X+Z MESMERISE: Internal and Z-MESMERISE: External detection. external detection. Highly non-disruptive. 0.25 µSv 0.00 µSv Restrictions to the use of Ionizing Radiation may apply No restriction www.h2020mesmerise.eu",
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"content": "2-stage detection direct detection standard solution CdTe solution RX RX - scintillator semi-conductor light +- @ room temperature photodiode + charges charges ~ 2000 charges ~ 20 000 charges @ 100 keV @ 100 keV",
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"content": "Image resolution Detailed view of an image from the ASTM F792 test piece acquired by a conventional detection system (left) and the multiple energy detector (right) with same acquisition parameters.",
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"content": "Information processing\n\n- ME calibration, superposition\n- Method using probability density\n- Density & Zeff Identification\n\n \n\nDual-enerey detector [« sandwich »\n\n \n \n \n \n \n\nicn Fcm 3m cm\n\n- blue : PTFE iteflon]\n- green: PE |polyeifylene)\n- rad: PORM (defrin]",
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"content": "X-MESMERISE expected features: A full body non-divest non-intrusive quick non-disruptive ultra-low dose x-ray scanner (FBS), usable upon consent by the final user, for internally and externally concealed commodities detection identifying the object and warning the operator: Non-divest: the final user does not need to divest outer clothes or belongings from pockets, etc. Non-intrusive: it is completely contactless and because the ATR shows the alert, it is not necessary to render and display an image to the operator Quick: the whole operation could be deployed in a very convenient layout for both the customer and the security service, taking less time than the current systems Non-disruptive: the operation takes place in a continuous moving belt maintaining a constant flow of passengers The dose per scan is under the limits according to the EU standard limits ( 1mSv per year) Automated Target Recognition System",
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"content": "Inspired by tumor segmentation models Train a CNN (Convolutional Neural Network) model for Semantic Segmentation.",
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"content": "Our model Overall Architecture: Deep Encoder-Decoder CNN-based (Convolutional Neural Network CNN) Given a feature representation obtained from the encoder network, dense pixel-wise prediction map is constructed through decoder network.",
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"content": "4.1 Quantitative Results Setups: Set 1: Training images: 49 Validation images: 8 Set 2: Training images: 29 Validation images: 28 Evaluation metrics: Global Accuracy (GA) – Pixels right Class Average Accuracy (CAA) – Proportion of Right Pixel per Class Intersection over Union (IoU) – Overlap between GT and Predicted Masks Dice coefficient (D) – Overlap with class 1 (narcotics positive)",
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"content": "4.1 Quantitative Results The importance of the number of training images Setups GA (%) CAA(%) IoU D SET 1 (49 99.16 71.10 0.6212 0.3519 training images) SET 2 (29 99.16 64.41 0.5761 0.2725 training images)",
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