Camera-based Image Forgery Localization using Convolutional Neural Networks

Camera fingerprints are precious tools for a number of image forensics tasks. A well-known example is the photo response non-uniformity (PRNU) noise pattern, a powerful device fingerprint. Here, to address the image forgery localization problem, we rely on noiseprint, a recently proposed CNN-based camera model fingerprint. The CNN is trained to minimize the distance between same-model patches, and maximize the distance otherwise. As a result, the noiseprint accounts for model-related artifacts just like the PRNU accounts for device-related non-uniformities. However, unlike the PRNU, it is only mildly affected by residuals of high-level scene content. The experiments show that the proposed noiseprint-based forgery localization method improves over the PRNU-based reference

Cross-collaborative supply chains. How logistics services contribute to social responsibility.

Abstract Purpose - The collaboration between profit and nonprofit entities has become a burning topic in supply chain management studies and corporate strategies. The world’s largest logistics service providers (LSPs) have been developing several practices improving social responsibility while collaborating with nonprofit actors. In particular, their core competences and offered services become extremely relevant in the context of humanitarian logistics initiatives. A key purpose of this article is to examine the projects currently undertaken by LSPs in humanitarian logistics. Methodology/Approach - This research follows a qualitative approach based on multiple case studies. Findings - The paper provides an overview of the leading LSPs’ involvement in humanitarian logistics and presents an analysis of their current “best practices” services in disaster relief with high impact in terms of social responsibility. Research Limitations/implications - There has been increased interest on the part of international academic and professional communities in humanitarian logistics. This study constitutes a platform for benchmarking analysis of logistics services to assure effective implementation of social responsibility principles. Originality/Value of paper - Humanitarian logistics is a rather new field in logistics management. This paper addresses the innovative socially responsible initiatives undertaken by the main international LSPs in the area of humanitarian logistics. Keywords - logistics services, logistics service providers, humanitarian logistics and supply chain management, disaster relief, social responsibility, profit/nonprofit collaboration Type of paper - Research pape

Target-adaptive CNN-based pansharpening

We recently proposed a convolutional neural network (CNN) for remote sensing image pansharpening obtaining a significant performance gain over the state of the art. In this paper, we explore a number of architectural and training variations to this baseline, achieving further performance gains with a lightweight network which trains very fast. Leveraging on this latter property, we propose a target-adaptive usage modality which ensures a very good performance also in the presence of a mismatch w.r.t. the training set, and even across different sensors. The proposed method, published online as an off-the-shelf software tool, allows users to perform fast and high-quality CNN-based pansharpening of their own target images on general-purpose hardware

A reliable order-statistics-based approximate nearest neighbor search algorithm

We propose a new algorithm for fast approximate nearest neighbor search based on the properties of ordered vectors. Data vectors are classified based on the index and sign of their largest components, thereby partitioning the space in a number of cones centered in the origin. The query is itself classified, and the search starts from the selected cone and proceeds to neighboring ones. Overall, the proposed algorithm corresponds to locality sensitive hashing in the space of directions, with hashing based on the order of components. Thanks to the statistical features emerging through ordering, it deals very well with the challenging case of unstructured data, and is a valuable building block for more complex techniques dealing with structured data. Experiments on both simulated and real-world data prove the proposed algorithm to provide a state-of-the-art performance

Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection

Local descriptors based on the image noise residual have proven extremely effective for a number of forensic applications, like forgery detection and localization. Nonetheless, motivated by promising results in computer vision, the focus of the research community is now shifting on deep learning. In this paper we show that a class of residual-based descriptors can be actually regarded as a simple constrained convolutional neural network (CNN). Then, by relaxing the constraints, and fine-tuning the net on a relatively small training set, we obtain a significant performance improvement with respect to the conventional detector

Sustainable supply chain management needs sustainable logistics services. The strategic role played by logistics service providers

Purpose – The purpose of this research is to examine the concept of sustainable service co-creation in triadic business relationships in logistics and supply chain management. More companies seek to develop sustainable solutions that would not be sustainable exclusively for themselves but for the supply chain they belong to. In doing that – especially when dealing with services – they may need the external support from logistics service providers (LSPs). This paper aims to explore the innovative initiatives undertaken by LSPs in triadic relationship management with their customers and suppliers while co-creating sustainable services along the supply chain. Design/methodology/approach – To investigate the research question, a systematic literature review and empirical exploratory investigation through case study will be conducted adopting the qualitative methodology, to explore trends and evolving paradigms. Findings – A literature review conducted in this paper enriches existing literature through an integration of sustainability in a viable system approach and logistics service provision, in particular, it investigates the ways in which sustainability is achieved. It is assumed that the triadic relationship among an LSP and its customers and suppliers requires significant modifications in collaboration and an innovative approach in operating procedures. Research limitations/implications – This paper is an exploratory study and limited in its scope to an example of a relationship that focuses mainly on three actors: the supplier, the LSP and the customer. However, it could be extended in terms of numbers of case studies investigated. Practical implications – The implications arising from the literature and the empirical research offer a range of current sustainable practices in the services sector. This could be a starting point for other research and company activities. Originality/value – There is little research that addresses the issue of sustainability and logistics service providers simultaneously, hence the present paper is meant to fill the gap by providing a foundation which actors of different supply chains could use as a benchmark. This study gives evidence of how logistics services may contribute to sustainable development. Key words – sustainable supply chain management, logistics service providers, viable system approach, co-creation, business relationship managemen