Neural network based hyperspectral imaging for substrate independent bloodstain age estimation

Giulietti, Nicola; Discepolo, Silvia; Castellini, Paolo; Martarelli, Milena

doi:10.1016/j.forsciint.2023.111742

Cited by 5 publications

(3 citation statements)

References 16 publications

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“…A Bayesian optimization technique for hyperparameter tuning, as detailed in [21], is utilized to determine the optimal numbers of layers, neurons per layer, and model hyperparameters that minimize the loss function. This technique of hyperparameter optimization is widely tested in various fields and is proven to be superior to other techniques, such as grid search and random search [22,23]. This technique performs training many times with different sets of numbers of layers, neurons, and hyperparameters.…”

Section: Ai-based Virtual Sensor For Ground Reaction Force Estimationmentioning

confidence: 99%

AI-Driven Virtual Sensors for Real-Time Dynamic Analysis of Mechanisms: A Feasibility Study

Fabiocchi,

Giulietti,

Carnevale

et al. 2024

Machines

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The measurement of the ground forces on a real structure or mechanism in operation can be time-consuming and expensive, particularly when production cannot be halted to install sensors. In cases in which disassembling the parts of the system to accommodate sensor installation is neither feasible nor desirable, observing the structure or mechanism in operation and quickly deducing its force trends would facilitate monitoring activities in industrial processes. This opportunity is gradually becoming a reality thanks to the coupling of artificial intelligence (AI) with design techniques such as the finite element and multi-body methods. Properly trained inferential models could make it possible to study the dynamic behavior of real systems and mechanisms in operation simply by observing them in real time through a camera, and they could become valuable tools for investigation during the operation of machinery and devices without the use of additional sensors, which are difficult to use and install. In this paper, the idea presented is developed and applied to a simple mechanism for which the reaction forces during operating conditions are to be determined. This paper explores the implementation of an innovative vision-based virtual sensor that, through data-driven training, is able to emulate traditional sensing solutions for the estimation of reaction forces. The virtual sensor and relative inferential model is validated in a scenario as close to the real world as possible, taking into account interfering inputs that add to the measurement uncertainty, as in a real-world measurement scenario. The results indicate that the proposed model has great robustness and accuracy, as evidenced by the low RMSE values in predicting the reaction forces. This demonstrates the model’s effectiveness in reproducing real-world scenarios, highlighting its potential in the real-time estimation of ground reaction forces in industrial settings. The success of this vision-based virtual sensor model opens new avenues for more robust, accurate, and cost-effective solutions for force estimation, addressing the challenges of uncertainty and the limitations of physical sensor deployment.

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Section: Ai-based Virtual Sensor For Ground Reaction Force Estimationmentioning

confidence: 99%

AI-Driven Virtual Sensors for Real-Time Dynamic Analysis of Mechanisms: A Feasibility Study

Fabiocchi,

Giulietti,

Carnevale

et al. 2024

Machines

Self Cite

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show abstract

“…Hence, the color change of blood was used to determine bloodstain TSD in the early 1900s . Since then, a series of methods, such as colorimetric analysis, spectroscopic techniques (e.g., visible absorption spectroscopy, infrared spectroscopy, Raman spectroscopy, hyperspectral imaging, , electron paramagnetic resonance spectroscopy, etc. ), and electrochemical methods , have been adopted for the investigation of the Hb degradation. ,− Nevertheless, the Hb ex vivo oxidation mechanism is complex, leading to the inaccuracy of the estimation results.…”

Section: Introductionmentioning

confidence: 99%

“…Since then, a series of methods, such as colorimetric analysis, spectroscopic techniques (e.g., visible absorption spectroscopy, infrared spectroscopy, Raman spectroscopy, hyperspectral imaging, , electron paramagnetic resonance spectroscopy, etc. ), and electrochemical methods , have been adopted for the investigation of the Hb degradation. ,− Nevertheless, the Hb ex vivo oxidation mechanism is complex, leading to the inaccuracy of the estimation results. The Hb ex vivo oxidation process can also lead to structural changes in red blood cells such as volume, surface area, perimeter, and height, as well as the nanomechanical features (e.g., the viscoelasticity), which have been explored by atomic force microscopy (AFM) .…”

Section: Introductionmentioning

confidence: 99%

Alkaline Phosphatase for Estimating the Time since Deposition of Blood Fingerprints by Scanning Electrochemical Microscopy

Chen,

Tian,

Sun

et al. 2023

Anal. Chem.

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Estimation of human bloodstains time since deposition using ATR-FTIR spectroscopy and chemometrics in simulated crime conditions

Mengual-Pujante,

Perán,

Ortiz

et al. 2024

Chemometrics and Intelligent Laboratory Systems

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Neural network based hyperspectral imaging for substrate independent bloodstain age estimation

Cited by 5 publications

References 16 publications

AI-Driven Virtual Sensors for Real-Time Dynamic Analysis of Mechanisms: A Feasibility Study

AI-Driven Virtual Sensors for Real-Time Dynamic Analysis of Mechanisms: A Feasibility Study

Alkaline Phosphatase for Estimating the Time since Deposition of Blood Fingerprints by Scanning Electrochemical Microscopy

Estimation of human bloodstains time since deposition using ATR-FTIR spectroscopy and chemometrics in simulated crime conditions

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