| 000 | 05544cam a2200505Ii 4500 | ||
|---|---|---|---|
| 999 |
_c96233 _d96233 |
||
| 001 | 96233 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230102112745.0 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 170621s2017 si a ob 101 0 eng d | ||
| 020 |
_a9789811038181 _q(electronic bk.) |
||
| 020 |
_a981103818X _q(electronic bk.) |
||
| 020 | _z9789811038174 | ||
| 020 | _z9811038171 | ||
| 040 |
_aN$T _cN$T _dN$T _dEBLCP _dGW5XE _dYDX _dUAB _dAZU _dUPM _dMERER _dESU _dOCLCQ _dCOO _dOCLCQ _dIOG _dES-MaUEC _bspa |
||
| 050 | 4 |
_aQA75.5 _bI566 2017 EB |
|
| 111 | 2 |
_aInternational Conference on Internet Computing in Science and Engineering _n(4th : _d2016 : _cHyderabad, India) |
|
| 245 | 1 | 0 |
_aInnovations in computer science and engineering : _bproceedings of the fourth ICICSE 2016 _cH.S. Saini, Rishi Sayal, Sandeep Singh Rawat, editors. |
| 264 | 1 |
_aSingapore _bSpringer _c[2017] |
|
| 264 | 4 | _c2017 | |
| 300 |
_a1 recurso en línea (xvii, 378 páginas) _bilustraciones |
||
| 336 |
_aTexto _btxt _2rdacontent |
||
| 337 |
_aelectrónico _bc _2rdamedia |
||
| 338 |
_arecurso electrónico _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF |
||
| 490 | 0 |
_aLecture notes in networks and systems _vvolume 8 |
|
| 500 | _aSpringerLink | ||
| 504 | _aIncluye referencias bibliográficas e índice | ||
| 505 | 0 | _aPreface; Organizing Committee; Patrons; Conference Chair; Conference Co-Chairs; Convenors; Co-Convenors; Conference Committee; Publicity Chair International; Publicity Chair National; Program and Publication Chair; Accommodation Committee; Advisory Board-International/National, Technical Program Committee; A Note from the Organizing Committee; Contents; About the Editors; 1 Comparative Study of Techniques and Issues in Data Clustering; Abstract; 1 Introduction; 2 Clustering in Data Mining; 2.1 Partitioning Clustering; 2.2 Density Based Clustering; 2.3 Model Based Clustering. | |
| 505 | 8 | _a1 Introduction1.1 Content Based Image Retrieval (CBIR); 2 Fast Discrete Curvelet Transform; 2.1 Curvelet Computation; 3 Implementation; 3.1 General Idea; 3.2 Detailed Description; 4 Results and Analysis; 4.1 Outputs; 4.2 Analysis; 5 Conclusion and Future Scope; References; 4 Compute the Requirements and Need of an Online Donation Platform for Non-monetary Resources Using Statistical Analyses; Abstract; 1 Introduction; 2 Literature Review; 2.1 Existing Frameworks Regarding Donor Behavior; 2.2 Marketing Activities of NGO Influencing Donor's Perception. | |
| 505 | 8 | _a2.3 Applying the Donor Knowledge to an Online Solution3 Result Analysis; 3.1 T-Test; 3.2 ANOVA Test; 3.3 Summary of Results; 4 Conclusion; References; 5 Enacting Segmentation Algorithms for Classifying Fish Species; Abstract; 1 Introduction; 1.1 Nearest Neighbor Classifier; 1.2 Watershed Algorithm; 2 Implementing Watershed Algorithm; 2.1 Load Image; 2.2 Morphological Transformation; 2.3 Adjustment; 2.4 Converting Image to Black and White; 2.5 Calculating BW Distance; 2.6 Applying Watershed; 3 Implementing Nearest Neighbor Classifier; 3.1 Load Image; 3.2 Initialize the Storage for Each Sample. | |
| 505 | 8 | _a2.4 Hierarchical Clustering3 Literature Survey; 3.1 Identification of Formation of Clusters; 3.2 Clustering Large Datasets; 3.3 Large Computational Time; 3.4 Efficient Initial Seed Selection; 3.5 Identification of Different Distance and Similarity Measures; 4 Summary of Clustering Approaches; 5 Conclusion; References; 2 Adaptive Pre-processing and Regression of Weather Data; Abstract; 1 Introduction; 2 Related Work; 3 Proposed Method; 4 Experimental Results; 5 Conclusion and Future Scope; References; 3 A Comparative Analysis for CBIR Using Fast Discrete Curvelet Transform; Abstract. | |
| 505 | 8 | _a3.3 Selecting Each Sample Region3.4 Converting rgb to l*a*b* Image; 3.5 Calculation of Mean a* and b* Values; 3.6 Performance Classification; 3.7 Clearing Value Distance; 4 Results and Discussions; 4.1 Watershed Algorithm; 4.2 Nearest Neighbor Classifier Algorithm; 5 Conclusion; References; 6 Pattern Based Extraction of Times from Natural Language Text; Abstract; 1 Introduction; 2 Existing Works; 3 Frame Work for Times Extraction; 3.1 Components Description; 4 Pattern Based Rules for Times Extraction; 5 Results; 6 Conclusion and Future Work; References. | |
| 520 | 3 | _aThe book is a collection of high-quality peer-reviewed research papers presented at the Fourth International Conference on Innovations in Computer Science and Engineering (ICICSE 2016) held at Guru Nanak Institutions, Hyderabad, India during 22 - 23 July 2016. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of data science and analytics, artificial intelligence and expert systems, mobility, cloud computing, network security, and emerging technologies. | |
| 588 | 0 | _aOnline resource; title from PDF title page (EBSCO, viewed June 23, 2017). | |
| 988 | _aEBOOK, EBSPRINGER_2017D | ||
| 650 | 7 |
_2embne _aOrdenadores _9138111 |
|
| 700 | 1 |
_aRawat, Sandeep Singh, _eeditor literario _9100799 |
|
| 700 | 1 |
_aSaini, H. S., _eeditor literario _9100797 |
|
| 700 | 1 |
_aSayal, Rishi, _eeditor literario _9100798 |
|
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-981-10-3818-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
||
| 998 |
_b02/2018 _dz _e- _zSI |
||