D
Deepti D. Shrimankar
Researcher at Visvesvaraya National Institute of Technology
Publications - 42
Citations - 716
Deepti D. Shrimankar is an academic researcher from Visvesvaraya National Institute of Technology. The author has contributed to research in topics: Automatic summarization & Wireless sensor network. The author has an hindex of 12, co-authored 37 publications receiving 416 citations.
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F-DES: Fast and Deep Event Summarization
TL;DR: A local-alignment-based FASTA approach to summarize the events in multiview videos as a solution of the aforementioned problems and successfully reduces the video content while keeping momentous information in the form of events.
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Eratosthenes sieve based key-frame extraction technique for event summarization in videos
TL;DR: An Eratosthenes Sieve based key-frame extraction approach for video summarization (VS) which can work better for real-time applications and outperform the state-of-the-art models on F-measure.
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Deep Event Learning boosT-up Approach: DELTA
TL;DR: Target, as well as subjective ratings, clearly indicate the potency of the proposed DELTA model, where it successfully reduces the video data, while keeping the important information as events, in the multi-view surveillance videos.
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Controllers in SDN: A Review Report
TL;DR: A review report on various available SDN controllers covering major popular controllers used in SDN paradigm and how the centralized decision capability of the controller changes the network architecture with network flexibility and programmability.
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LAR-CH: A Cluster-Head Rotation Approach for Sensor Networks
TL;DR: A load-aware rotation of CH (LAR-CH) approach is proposed, which sets a dynamic threshold for CH-rotation to reduce the premature death of CH nodes and simulation results show that LAR-CH reduces the prematureDeath ofCH nodes by 40% compared with the low-energy adaptive clustering hierarchy protocol.