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Anirban Mitra

dblp:56/5158 · DBLP profile ↗
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6ranked-venue papers
1as first author
2since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 1 first-author · 1 since 2021Computer networks · 1Databases, data management, data science and information retrieval · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%
Computer networks
1 paper
Internet of things and sensor networks · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems › wireless communication › wireless sensor networks
wireless sensor node
0.112005
Splitting the sensor node · SenSys 2005

Methods — techniques the papers use, named apart from their topics

FFT benchmark · 0.1
YearPublicationVenuePosition
2026 Multi-relational knowledge graph-based evolutionary multi-level personalized attention GNN for recommendation systems
Subhankar Guha, Bhramara Bar Biswal, Anirban Mitra
Knowl. Inf. Syst.3
2021 A novel intuitionistic fuzzy soft set entrenched mammogram segmentation under Multigranulation approximation for breast cancer detection in early stages
Swarup Kr Ghosh, Anirban Mitra, Anupam Ghosh
Expert Syst. Appl.2
2019 Blood vessel segmentation of retinal image using Clifford matched filter and Clifford convolution
Somasis Roy, Anirban Mitra, Sudipta Roy 0002, Sanjit Kumar Setua
Multim. Tools Appl.2
2018 Thermal Comfort Index Estimation and Parameter Selection Using Fuzzy Convolutional Neural Network
Anirban Mitra, Arjun Sharma, Sumit Sharma 0002, Sudip Roy 0001
ICANN (1)1
2018 Estimation of Air Quality Index from Seasonal Trends Using Deep Neural Network
Arjun Sharma, Anirban Mitra, Sumit Sharma 0002, Sudip Roy 0001
ICANN (3)2
2005 Splitting the sensor node
abstract
The current trend of computationally intensive applications such as audio capture, FFT, image sensing, motion detection, feature extraction and cepstrum calculations being ported to the sensor domain, alludes towards the need to handle copious amounts of data in comparison to rudimentary temperature and humidity sensing applications. Developing a split architecture based sensor platform is an effective and efficient methodology to reach the crucial goal of in-situ processing of data. Resulting in a direct reduction in the amount of information needed to be transmitted over the wireless links. The Split-Node-Architecture (SNA) which we develop addresses this very crucial aspect of sensor network design. The suitability of employing the SNA architecture is demonstrated by its performance metrics obtained by running a 128point FFT benchmark. The higher throughput, of the SNA architecture enables faster data processing upto 24 times that of the Atmel AVR architecture (MICA). Additionally a 29% improvement in power efficiency vis a vis popular sensor platforms, tilts the scales unambiguously in favor of the SNA. The low power consumption of the Co-S module, a part of SNA, results in savings upto 6uJ per 128 point FFT operation when compared to the Stargate (Intel PXA 255).
Anirban Banerjee, Anirban Mitra, Walid A. Najjar
SenSys2