An Extensive Analysis of Amphibious Drones for Surveillance DOI

J. Surendiran,

S. Subburam,

Fathima. S. K

et al.

Published: Oct. 8, 2024

Language: Английский

Improving burn diagnosis in medical image retrieval from grafting burn samples using B-coefficients and the CLAHE algorithm DOI Creative Commons
Pramod Rangaiah, B. P. Pradeep Kumar, Robin Augustine

et al.

Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 99, P. 106814 - 106814

Published: Sept. 9, 2024

Language: Английский

Citations

3
Comparative Assessment of Machine Learning Models for Predicting Glucose Intolerance Risk DOI
B. P. Pradeep Kumar,

H. M. Manoj

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(7)

Published: Sept. 21, 2024

Language: Английский

Citations

3
Gauging Deep Learning Archetypal Effectiveness in Haematological Reclamation DOI
B. P. Pradeep Kumar,

J. Ravikumar

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(7)

Published: Oct. 15, 2024

Language: Английский

Citations

2
A Systemic Review on Automatic Acoustic Scene Classification DOI

J. Surendiran,

P.B Edwin Prabhakar,

Mohamad Ibrahim

et al.

Published: Oct. 8, 2024

Language: Английский

Citations

1
Improved Magnetic Resonance Image Reconstruction using Compressed Sensing and Adaptive Multi Extreme Particle Swarm Optimization Algorithm DOI Creative Commons

Moureen Nalumansi,

Elijah Mwangi,

George Kamucha

et al.

International Journal of Electrical and Electronics Research, Journal Year: 2024, Volume and Issue: 12(2), P. 393 - 402

Published: April 30, 2024

One powerful technique that can offer a thorough examination of the body's internal structure is magnetic resonance imaging (MRI). MRI's lengthy acquisition times, however, may restrict its clinical usefulness, particularly in situations where time essence. Compressed sensing (CS) has emerged as potentially useful method for cutting down on MRI times; nevertheless, effectiveness CS-MRI dependent selection sparsity-promoting algorithm and sampling scheme. This research paper presents novel based adaptive multi-extreme particle swarm optimization (AMEPSO) dual tree complex wavelet transform (DTCWT) fast image resonance. The uses AMEPSO order to maximize pattern minimize reconstruction error, while also exploiting sparsity MR images DTCWT domain improve directional selectivity shift invariance. MATLAB software was used simulation proposed method. In comparison with optimized-DTCWT (PSODTCWT) algorithms, respectively, results demonstrated an improvement peak signal-to-noise ratio 8.92% 15.92% higher structural similarity index measure 3.69% 7.5%. Based these improvements, could make high-quality, real-time possible, which might detection treatment medical conditions increase throughput machines.

Language: Английский

Citations

0
Eye Hypertension Disorder Through Ensemble Frame Networks: A Novel Approach for Early Identification and Segmentation DOI

T R Yashavanth,

Wahida Banu,

Rathan Kumar

et al.

SN Computer Science, Journal Year: 2024, Volume and Issue: 5(8)

Published: Nov. 20, 2024

Language: Английский

Citations

0
An Extensive Analysis of Amphibious Drones for Surveillance DOI

J. Surendiran,

S. Subburam,

Fathima. S. K

et al.

Published: Oct. 8, 2024

Language: Английский

Citations

0