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Titlebook: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications; Azah Kamilah Muda,Yun-Huoy Choo,Sargur N. Srihar

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1860-949X Computational Intelligence in Digital Forensics; in both theoretical and application papers related to novel discovery in intelligent forensics. The chapters are further o978-3-319-38181-7978-3-319-05885-6Series ISSN 1860-949X Series E-ISSN 1860-9503
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Limitations and future researchcomplete and automatic biometric identification or recognition systems have been built accordingly. This chapter presents a study of the impacts of using some biometric modalities in forensic applications. Although biometrics identification replaces human work with computerized and automatic systems
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Limitations and future researchive’ forensics which comprises proactive forensics approaches capable of digitally investigating an incident as it occurs. However, information exchange using ICT facilities has reduced the world into a global village without eliminating the linguistic diversity on the planet. Moreover, existing dig
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Strategic Thinking for Turbulent Timesosure to distressing and offensive materials are of major concerns. Lack of technological support for processing large amount of offensive data makes the analytical procedure quite time consuming and expensive. Thus, it results in a degradation of mental health of concerned investigators. Backlog in
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Corporations in the Global Economyd multimodal hand based biometrics (e.g. hand geometry, palmprint and hand vein) with several feature extraction, database and verification methods have been discussed with 2D, 3D and infrared images.
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https://doi.org/10.1057/9780230006089ess the specimen of data. Focusing only on age determination, it covers all range of techniques from physical maturity measurement on growth, development of dentition, development of lenses protein, mathematical computation and soft computing and artificial intelligence approach. There are five aspe
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Strategic Directions and Views, into account the shape of the spectra. The analyzed sample will take the class of the closest pattern. Spectra are previously standardized in order to eliminate the variation of the slope of the curves caused by the dispersion and the variation in the particle size. With this purpose, the standard
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