Lecture Notes in Computer Science Journal Impact Factor & Information

Publisher: Springer Verlag

Journal description

The series Lecture Notes in Computer Science (LNCS), including its subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics (LNBI), has established itself as a medium for the publication of new developments in computer science and information technology research and teaching - quickly, informally, and at a high level. The cornerstone of LNCS's editorial policy is its unwavering commitment to report the latest results from all areas of computer science and information technology research, development, and education. LNCS has always enjoyed close cooperation with the computer science R & D community, with numerous renowned academics, and with prestigious institutes and learned societies. Our mission is to serve this community by providing a most valuable publication service.

Current impact factor: 0.51

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2005 Impact Factor 0.302
2004 Impact Factor 0.251
2002 Impact Factor 0.515
2001 Impact Factor 0.415
2000 Impact Factor 0.253
1999 Impact Factor 0.53

Impact factor over time

Impact factor

Additional details

5-year impact 0.00
Cited half-life 0.00
Immediacy index 0.00
Eigenfactor 0.00
Article influence 0.00
Website Lecture Notes in Computer Science website
Other titles Lecture notes in computer science, Lecture notes in artificial intelligence, Lecture notes in computer science
ISSN 0302-9743
OCLC 3719235
Material type Series, Internet resource
Document type Journal / Magazine / Newspaper, Internet Resource

Publisher details

Springer Verlag

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on pre-print servers such as arXiv.org
    • Author's post-print on author's personal website immediately
    • Author's post-print on any open access repository after 12 months after publication
    • Publisher's version/PDF cannot be used
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany link to published version (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
  • Classification

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Introducing a number of innovative and powerful coding tools, the High Efficiency Video Coding (HEVC) standard promises double compression efficiency, compared to its predecessor H.264, with similar perceptual quality. The increased computational time complexity is an important issue for the video coding research community as well. An attempt to reduce this complexity of HEVC is adopted in this paper, by efficient selection of appropriate block-partitioning modes based on motion features and the saliency applied to the difference between successive image blocks. As this difference gives us the explicit visible motion and salient information, we develop a cost function by combining the motion features and image difference salient feature. The combined features are then converted into area of interest (AOI) based binary pattern for the current block. This pattern is then compared with a previously defined codebook of binary pattern templates for a subset of mode selection. Motion estimation (ME) and motion compensation (MC) are performed only on the selected subset of modes, without exhaustive exploration of all modes available in HEVC. The experimental results reveal a reduction of 42% encoding time complexity of HEVC encoder with similar subjective and objective image quality.
    Lecture Notes in Computer Science 11/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: Machine vision is now being extensively used for defect detection in the manufacturing process of collagen-based products such as sausage skins. At present the industry standard is to use a LabView software environment to manage and detect any defects in the collagen skins. Available data corroborates that this method allows for false positives to appear in the results which is responsible for reducing the overall system performance and resulting wastage of resources. Hence novel criteria were added to enhance the current techniques. The proposed improvements aim to achieve a higher accuracy and flexibility in detecting both true and false positives by utilizing a function that probes for the color deviation and fluctuation in the collagen skins. After implementation of the method in a well-known Australian company, investigational results demonstrate an average 26% increase in the ability to detect false positives with a corresponding substantial reduction in operating cost.
    Lecture Notes in Computer Science 11/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: We consider the classic setting of Capacitated Vehicle Rout- ing Problem (CVRP): single product, single depot, demands of all cus- tomers are identical. It is known that this problem remains strongly NP-hard even being formulated in Euclidean spaces of fixed dimension. Although the problem is intractable, it can be approximated well in such a special case. For instance, in the Euclidean plane, the problem (and it’s several modifications) have polynomial time approximation schemes (PTAS). We propose polynomial time approximation scheme for the case of R3
    Lecture Notes in Computer Science 11/2015; 9486:178-191.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Human identification at a distance remains a challenging problem. Two biometric sources that are available in such situations are gait and face. In this paper, we present a new approach that utilizes and integrates information from frontal gait and face at the feature level. A novel kernel coupled mapping method is introduced to project both the gait features and the face features into a unified subspace where the heterogeneous modalities are transformed into the homologous features naturally. Moreover, the proposed feature level fusion scheme is compared with the match score level fusion schemes (Sum, Max and Product rules) and two feature level fusion schemes. The experimental results demonstrate that the proposed feature level fusion scheme outperforms the match score level and the other two feature level fusion schemes.
    Lecture Notes in Computer Science 11/2015; 9428:544-552.
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents an approach to construct a verified virtual prototyping framework of embedded software. The machine code executed on a simulated target architecture can be proven to provide the same results as the real hardware, and the proof is verified with a theorem prover. The method consists in proving each instruction of the instruction set independently, by proving that the execution of the C code simulating an instruction yields an identical result to that obtained by a formal executable model of the processor architecture. This formal model itself is obtained through an automated translation process from the architecture specifications. Each independent proof draws a number of lemmas from a generic lemma library and also uses the automation of inversion tactics in the theorem prover. The paper presents the proof of the ARM architecture version 6 Instruction Set Simulator of the SimSoC open source simulator, with all of the proofs being verified by the Coq proof ssistant, using automated tactics to reduce manual proof development.
    Lecture Notes in Computer Science 11/2015; LNCS 9409:106. DOI:10.1007/978-3-319-25942-0

  • Lecture Notes in Computer Science 11/2015;
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, the target-oriented overall process optimization (TOPO) strategy is for the first time applied to a six-unit production process of gardenia extract, in order to improve the product quality during the multistage batch manufacturing process. The optimization action is performed actively and iteratively from the second stage as the process continued, giving each stage the maximum probability for the product quality meeting the specified requirements. Simulation results demonstrated that TOPO could lead the product quality towards the predefined target and mitigate the variations from the raw materials.
    Lecture Notes in Computer Science 10/2015; 9243:267-276. DOI:10.1007/978-3-319-23862-3_26