Eye Tumour Detection Using Deep Learning

Sinha, Avigyan; Aneesh, R P; S, Nazneen N.

doi:10.1109/icbsii51839.2021.9445172

Cited by 15 publications

(4 citation statements)

References 8 publications

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“…During training, ResNet learns to map the extracted features from CWT to the target properties, effectively learning the complex relationships within the data. The integration of CWT and ResNet creates an iterative framework that can be refined over time with the enhanced band of seismic data and its derived attributes …”

Section: Methodsmentioning

confidence: 99%

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ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

Akram,

Akhter,

et al. 2024

ACS Omega

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The endeavor to explore and characterize oil and gas reservoirs presents significant challenges due to the inherent heterogeneities that are further compounded by the existence of thin sand layers encapsulated in shale strata. This complexity is intensified by limited and low-resolution seismic data, missing critical well-log information, and inaccessible angle stack data. Conventional reservoir classification approaches have struggled to address these issues, primarily due to their limitations in handling missing data effectively and, hence, precise estimations. This study focuses on the characterization of thin, heterogeneous potential sands of the B-interval within the Lower Goru Formation, a proven gas reservoir in the Badin area. The reservoir sands with varying thicknesses are assessed in detail for their optimized description and field productions by handling challenges, including low seismic resolutions, heterogeneities, and missing data sets. An innovative solution is developed based on the integration of continuous wavelet transform (CWT) and machine learning (ML) techniques for the approximation of missing data sets, i.e., S-wave (DTS), along with enhanced elastic and petrophysical properties. The improved properties are augmented by the high resolution attained by CWT and captured variability more profoundly through the implication of residual neural networks (ResNet). The limitations of conventional approaches are harnessed by ML solutions that operate with limited input data and deliver significantly improved results in characterizing enigmatic thin sand reservoirs. The high-frequency petroelastic properties reliably determined the thin heterogeneous potential sand bodies and illuminated a channelized play fairway that can be tested for additional wells with low-risk involvement.

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Section: Methodsmentioning

confidence: 99%

“…The integration of CWT and ResNet creates an iterative framework that can be refined over time with the enhanced band of seismic data and its derived attributes. 67 …”

Section: Methodsmentioning

confidence: 99%

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

Akram,

Akhter,

et al. 2024

ACS Omega

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“…Experiments using GoogLeNet generate more precise results than ResNet-50. Avigyan Sinha et al [9] proposed a method for detecting melanocytic tumors of the iris. Models of the Miles Eye Camera 24MP and the CRCS-FH4 Premium Professional Chinrest/Camera are used in this experiment.…”

Section: IImentioning

confidence: 99%

Early Detection of Eye Disease Using CNN

Erdin¹,

Patel²

2023

IJRASET

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The eyes perform an essential part of life. The eye is one of the organs that assist humans learn about their natural environments and collect information from them. Almost everywhere in the world, the frequency of eye disease has increased, needing a serious response. Immediate eye detection will be invaluable assistance in offering further treatment to prevent blindness. In this study, a Convolution Neural Network model is used for identifying eye diseases. This research aims to categorize human eyes into four categories: trachoma, conjunctivitis, cataract, and healthy. The investigation got an accuracy of 88.36%, while the CNN model evaluation provided Precision of 89.25%, Recall of 88.75%, and F1 Score of 88.5%. Based on the accuracy and evaluation results, this system can be used for the early detection of multiple eye diseases. Several random samples were also used for testing in this investigation. The test results indicate that this system is functional.

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“…Some authors have used Hough transform for circle detection. Sinha and Aneesh [22] applied it to detect the presence of tumors in circular eyeball and iris regions. Huan et al [23] proposed using transform to detect vehicle logos in open scenarios.…”

Section: Related Workmentioning

confidence: 99%

Improving the competitiveness of aircraft manufacturing automated processes by a deep neural network

Ruiz¹,

Díaz²,

González³

et al. 2023

ICA

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The accuracy and reliability requirements in aerospace manufacturing processes are some of the most demanding in industry. One of the first steps is detection and precise measurement using artificial vision models to accurately process the part. However, these systems require complex adjustments and do not work correctly in uncontrolled scenarios, but require manual supervision, which reduces the autonomy of automated machinery. To solve these problems, this paper proposes a convolutional neural network for the detection and measurement of drills and other fixation elements in an uncontrolled industrial manufacturing environment. In addition, a fine-tuning algorithm is applied to the results obtained from the network, and a new metric is defined to evaluate the quality of detection. The efficiency and robustness of the proposed method were verified in a real production environment, with 99.7% precision, 97.6% recall and an overall quality factor of 96.0%. The reduction in operator intervention went from 13.3% to 0.6%. The presented work will allow the competitiveness of aircraft component manufacturing processes to increase, and working environments will be safer and more efficient.

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Eye Tumour Detection Using Deep Learning

Cited by 15 publications

References 8 publications

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

ResNet and CWT Fusion: A New Paradigm for Optimized Heterogeneous Thin Reservoir Evaluation

Early Detection of Eye Disease Using CNN

Improving the competitiveness of aircraft manufacturing automated processes by a deep neural network

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