Somnath Bera

dblp:180/7475 · DBLP profile ↗
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8ranked-venue papers
3as first author
6since 2021 · last 2025
—ORCID · conflict

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

Theory of computation · 4 · 2 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021
YearPublicationVenuePosition
2025 Isolated word recognition based on a hyper-tuned cross-validated CNN-BiLSTM from Mel Frequency Cepstral Coefficients
Bachchu Paul, Santanu Phadikar, Somnath Bera, Tanushree Dey, Utpal Nandi
Multim. Tools Appl.3
2024 Machine learning approach of speech emotions recognition using feature fusion technique
Bachchu Paul, Somnath Bera, Tanushree Dey, Santanu Phadikar
Multim. Tools Appl.2
2024 Fly: Femtolet-based edge-cloud framework for crop yield prediction using bidirectional long short-term memory
abstract
Abstract Crop yield prediction is a crucial area in agriculture that has a large impact on the economy of a country. This article proposes a crop yield prediction framework based on Internet of Things and edge computing. We have used a fifth generation network device referred to as femtolet as the edge device. The femtolet is a small cell base station that has high storage and high processing ability. The sensor nodes collect the soil and environmental data, and then the collected data is sent to the femtolet through the microcontrollers. The femtolet retrieves the weather‐related data from the cloud, and then processes the sensor data and weather‐related data using Bi‐LSTM. The femtolet after processing the data sends the generated results to the cloud. The user can access the results from the cloud to predict the suitable crop for his/her land. This is observed that the suggested framework provides better accuracy, precision, recall, and F1‐score compared to the state‐of‐the‐art crop yield prediction frameworks. This is also demonstrated that the use of femtolet reduces the latency by ˜25% than the conventional edge‐cloud framework.
Tanushree Dey, Somnath Bera, Bachchu Paul, Debashis De, Anwesha Mukherjee, Rajkumar Buyya
Softw. Pract. Exp.2
2023 An array P system based on a new variant of pure 2D context-free grammars
abstract
Pure 2D context-free grammar (P2DCFG) with an independent mode of array rewriting, was recently introduced and named as IP2DCFG. Here we consider a variant of IP2DCFG, called (l/u)IP2DCFG, by requiring rewriting of the leftmost (respy. uppermost) symbol in every row (respy. column) of an array, with the symbol having a rewriting rule in a given set of pure context-free rules. We introduce an array P system with (l/u)IP2DCFG kind of rules and array rewriting in its membranes. When two membranes are used in the array P system, the array generative power is increased compared to using a single membrane.
Somnath Bera, Atulya K. Nagar, Sastha Sriram, K. G. Subramanian 0001
Theor. Comput. Sci.1
2023 E-CropReco: a dew-edge-based multi-parametric crop recommendation framework for internet of agricultural things
Somnath Bera, Tanushree Dey, Anwesha Mukherjee, Rajkumar Buyya
J. Supercomput.1
2021 Parikh Word Representable Graphs and Morphisms
Nobin Thomas, Lisa Mathew, Somnath Bera, Atulya K. Nagar, K. G. Subramanian 0001
DLT3
2020 On Commuting Parikh q-Matrices
abstract
This paper investigates properties of words such that their Parikh q-matrices commute. For any two words [Formula: see text], the concept of q-weak ratio property between u and v is introduced. Based on this property a necessary and sufficient condition for the Parikh q-matrices of any two words over binary alphabet to commute is given. This paper also provides a special class of words over an arbitrary alphabet ∑ k such that their Parikh q-matrices commute.
Somnath Bera, Kalpana Mahalingam
Fundam. Informaticae1
2018 Order of weak M-relation and Parikh matrices
Wen Chean Teh, K. G. Subramanian 0001, Somnath Bera
Theor. Comput. Sci.3