Free 2018 IEEE (CSE) synopsis of students requested papers

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Automatic Annotation of Text with Pictures

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Aim: a novel application has emerged that automatically adds pictures to text. Objectives: Is to reduce a reader’s cognitive information processing load1 by showing relevant pictures along with input text. A reader can quickly and easily decide if the text information deserves a closer look. Existing System: Here, provides a detailed comparison of eight well-known picturing systems. 1. WordsEye,17 a text-to-3D-scene rendering system, parses text into a semantic representation and creates a 3D rendering (a scene). 2. Story Picturing Engine9 extracts keywords and matches words to a labeled image database as part of the process of story illustration. 3. ROC-MMS for Complex Sentences12 produces a multimodal (text and pictures) summary of sentences. 4. Simple Sentence Picturing18 is an effort to investigate the idea that pictures can convey simple sentences across language barriers. 5. Enriching Textbooks19 matches sections of a textbook to Internet images...
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A Comprehensive Study of the Effect of Spatial Resolution and Color of Digital Images on Vehicle Classification

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Aim: To provide an answer for the question: what are the best values for these two properties (spatial resolution and color) of digital cameras to use in vision-based vehicle classification systems? In other words, how many pixels are sufficient to build an accurate vision-based vehicle classification system? Aim: To study the effect of spatial resolution on the accuracy and performance of image classification methods. Proposed System: present a comprehensive study of the effect of these two spatial characteristics ( Dimension and color ) of digital images on the vision-based vehicle classification process in terms of accuracy and performance. For Bag-of-Visual Words (BoVW) [13], Vector of Locally Aggregated Descriptors (VLAD) [14] and Fisher Vector (FV) [15] it is recommended to use the DSIFT descriptor. The ResNet/Convolutional Neural Network (CNN), architecture is considered the top classification method with an accuracy rate of 95.12% compare to BoVW, VLAD an...
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Inference Attack Resistant E Healthcare Cloud System with Fine Grained Access Control

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Aim: to systematically construct a secure and privacy preserving e-health cloud system, so that it is immune to the inference attack and runs efficiently. to protect the E-Healthcare data with fine-grained access control, the data can be either numerical or string value. Proposed system: proposed two-layer encryption scheme In the first-layer encryption, paper propose to define a specialized access policy for each data attribute in the EHR, generate a secret share or every distinct role attribute, and reconstruct the secret to encrypt each data attribute, which ensures a fine-grained access control, saves much encryption time, and conceals the frequency of role attributes occurring in the EHR. In the second-layer encryption, paper propose to preserve the privacy of role attributes and access policies used in the first-layer encryption. Specifically, merge the first-layer access policies, add noise to the merged access policy, and encrypt the first-layer access policies un...
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