QUANTITATIVE ASSESSMENT OF DIABETIC MACULAR EDEMA USING FLUORESCEIN LEAKAGE MAPS Abstract?Diagnosis of Diabetic Macular Edema (DME) from Fundus Fluorescein Angiography (FFA) image sequences is a standard clinical practice. Nevertheless, current methods depend on subjective evaluation of the amount of fluorescein leakage in the images which lack reproducibility and require well-trained grader. In this work,< Final...
Query-Adaptive Image Search With Hash Codes Abstract?Scalable image search based on visual similarity has been an active topic of research in recent years. State-of-the-art solutions often use hashing methods to embed high-dimensional image features into Hamming space, where search can be performed in real-time based on Hamming distance of compact hash codes. Unlike traditional metrics<...
Quey based aggreculture details Abstract? Quey based aggreculture details. In this paper, we study row-based detailed placement refinement for triple patterning lithography (TPL), which asks to find a refined detailed placement solution as well as a valid TPL layout decomposition under the objective of minimizing the number of stitches and the half-perimeter wirelength. Our problem…
Radio Database Compression for Accurate Energy-Efficient Localization in Fingerprinting Systems Abstract? Location fingerprinting is a positioning method that exploits the already existing infrastructures such as cellular networks or WLANs. Regarding the recent demand for energy efficient networks and the emergence of issues like green networking, we propose a clustering technique to compress the radio database…
RCDA: Recoverable Concealed Data Aggregation for Data Integrity in Wireless Sensor Networks Abstract? RCDA: Recoverable Concealed Data Aggregation for Data Integrity in Wireless Sensor Networks. Recently, several data aggregation schemes based on privacy homomorphism encryption have been proposed and investigated on wireless sensor networks. These data aggregation schemes provide better security compared with traditional aggregation…
Real-Time People Tracking in a Camera Network Abstract?We present an approach to track several subjects from video sequences acquired by multiple cameras in real time. We address the key concerns of real time performance and continuity of tracking in overlapping and nonoverlapping fields of view. Each human subject is represented by a parametric ellipsoid having…
Real-Time Scheduling with Security Enhancement for Packet Switched Networks Abstract? Real-time network applications depend on schedulers to guarantee the quality of service (QoS). Conventional real-time schedulers focus on the timing constraints but are much less effective in satisfying the security requirements. < Final Year Projects >In this paper, we propose an adaptive security-aware scheduling system…
Realtime Scheduling with security enhancement in packet switched networks Abstract? Real-time network applications depend on schedulers to guarantee the quality of service (QoS). Conventional real-time schedulers focus on the timing constraints but are much less effective in satisfying the security requirements. < Final Year Project > In this paper, we propose an adaptive security-aware scheduling…
Recognition of Handwritten Devnagari Characters through Segmentation and Artificial neural networks Abstract?A segmentation based adaptive approach for the learning and recognition of single person’s handwritten text. The approach is incorporated into an automated intelligent system for scanning of handwritten text on a paper and converting it into a text file. < Final Year Projects >It…
Recognizing Realistic Actions from Videos in the Wild Abstract? Recognizing Realistic Actions from Videos in the Wild. In this paper, we present a systematic framework for recognizing realistic actions from videos ?in the wild?. Such unconstrained videos are abundant in personal collections as well as on the Web. Recognizing action from such videos has not…
Reduced-Complexity Robust MIMO Decoders Abstract? Reduced-Complexity Robust MIMO Decoders. We propose a robust near maximum-likelihood (ML) decoding metric that is robust to channel estimation errors and is near optimal with respect to symbol error rate (SER). The solution involves an exhaustive search through all possible transmitted signal vectors; this search has exponential complexity, < Final...
