1 citations · 1 across the 1 of their papers we have counts for
5 papers
A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends
Saptarshi Sengupta, Sanchita Basak, Pallabi Saikia +5
Deep learning has solved a problem that as little as five years ago was thought by many to be intractable - the automatic recognition of patterns in data; and it can do so with acc…
Chaotic Quantum Double Delta Swarm Algorithm using Chebyshev Maps: Theoretical Foundations, Performance Analyses and Convergence Issues
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
Quantum Double Delta Swarm (QDDS) Algorithm is a new metaheuristic algorithm inspired by the convergence mechanism to the center of potential generated within a single well of a sp…
QDDS: A Novel Quantum Swarm Algorithm Inspired by a Double Dirac Delta Potential
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
In this paper a novel Quantum Double Delta Swarm (QDDS) algorithm modeled after the mechanism of convergence to the center of attractive potential field generated within a single w…
Learning to track on-the-fly using a particle filter with annealed- weighted QPSO modeled after a singular Dirac delta potential
Saptarshi Sengupta, Richard Alan Peters
This paper proposes an evolutionary Particle Filter with a memory guided proposal step size update and an improved, fully-connected Quantum-behaved Particle Swarm Optimization (QPS…
Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised,…