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Deep Learning-Based Conjunctival Melanoma Detection Using Ocular Surface Images
(
springer link
, 2023 , Article)
The human eye could be affected with conjunctival melanoma, which indicates a fatal malignant growth of the eye. Being a very rare disease, there exists a lack of related data in the literature. Also, very few studies ...
RamanNet: a generalized neural network architecture for Raman spectrum analysis
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds of materials. This sort of molecule fingerprinting has thus led to the widespread application of ...
Edge Detection with multi-scale representation and refined Network
(
Institution of Engineering and Technology
, 2022 , Conference Paper)
Edge detection is a representation of boundaries between objects and regions in an image. Due to the variations of types, scales, intensities as well as background, the detection of these boundaries represents a challenge ...
BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge ...
Development of deep learning framework to predict physicochemical properties for Ionic liquids
(
Elsevier
, 2023 , Book chapter)
In this paper, a deep learning-based group contribution approach has been developed to identify the optimum structure for ionic liquids (ILs) and to maximize the CO2 absorption capacity. The suggested methodology demonstrates ...
Computational methods for automated analysis of corneal nerve images: Lessons learned from retinal fundus image analysis
(
Elsevier
, 2020 , Article Review)
Corneal and retinal imaging provide a descriptive view of the nerve and vessel structure present inside the human eye, in a non-invasive manner. This helps in ocular, or other, disease identification and diagnosis. However, ...
Smartphone-based diabetic retinopathy severity classification using convolution neural networks
(
Springer
, 2021 , Conference Paper)
With diabetes growing at an alarming rate, changes in the retina causes a condition called diabetic retinopathy which eventually leads to blindness. Early detection of diabetic retinopathy is the best way to provide good ...
Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters
(
Elsevier
, 2023 , Article)
According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning ...
Estimating Blood Glucose Levels Using Machine Learning Models with Non-Invasive Wearable Device Data
(
IOS Press BV
, 2023 , Conference Paper)
In 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ...
AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
(
Ain Shams University
, 2023 , Article)
Internet of Things (IoT) and Artificial Intelligence (AI) technologies are currently replacing the traditional methods of handling buildings, infrastructure, and facilities design, control, and maintenance due to their ...