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A Probabilistic Particle Tracking Framework for Guided and Brownian Motion Systems with High Particle Densities
This paper presents a new framework for particle tracking based on a Gaussian Mixture Model (GMM). It is an extension of the state-of-the-art...
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A Generative Modeling Approach for Interpreting Population-Level Variability in Brain Structure
Understanding how neural structure varies across individuals is critical for characterizing the effects of disease, learning, and aging on the brain....
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Interface engineering of ferroelectric-gated MoS2 phototransistor
Two-dimensional (2D) layered materials have received significant attention owing to their unique crystal structures as well as outstanding optical...
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Concatenated deep features with modified LSTM for enhanced crop disease classification
In the agriculture industry, which is the backbone of our country, attaining healthy crops is a critical task. Unidentified crop diseases can cause...
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Coupled continuum damage mechanics and crystal plasticity model and its application in damage evolution in polycrystalline aggregates
In the present study, damage initiation and growth in a polycrystalline aggregate are investigated. In this regard, an anisotropic continuum damage...
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Microscopic image super resolution using deep convolutional neural networks
Recently, deep convolutional neural networks (CNNs) have achieved excellent results in single image super resolution (SISR). Owing to the strength of...
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Review, Limitations, and future prospects of neural network approaches for brain tumor classification
Brain tumor classification (BTC) using magnetic resonance imaging (MRI) are very important for the early detection of brain tumors (BTs). It makes a...
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A review on deep learning in medical image analysis
Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical...
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Recent progress of hafnium oxide-based ferroelectric devices for advanced circuit applications
Hafnium oxide-based ferroelectric field-effect-transistors (FeFET), which combine super-steep logical switching and low power non-volatile memory...
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Reverse Engineering Flash EEPROM Memories Using Scanning Electron Microscopy
In this article, a methodology to extract Flash EEPROM memory contents is presented. Samples are first backside prepared to expose the tunnel oxide...
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Application of machine learning method in optical molecular imaging: a review
Optical molecular imaging (OMI) is an imaging technology that uses an optical signal, such as near-infrared light, to detect biological tissue in...
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An efficient adaptive histogram based segmentation and extraction model for the classification of severities on diabetic retinopathy
Diabetic retinopathy (DR) is an important retinal disease, which occurs commonly among diabetic patients. This disease severely injures the basic...
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Focal Stacking for Crystallization Microscopy
Automated image analysis of protein crystallization images is one of the important research areas. For proper analysis of the microscopic images, it...
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Current Trends in Development of Optical Metrology
AbstractThis review offers the reader some of the achievements of modern optical metrology. Over the past decades, it has become possible to make a...
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An efficient multi class Alzheimer detection using hybrid equilibrium optimizer with capsule auto encoder
Alzheimer is an advanced nervous brain disease. In old aged people, Alzheimer is also causing the death. The earlier prediction of Alzheimer’s...
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Deep Learning for Isotropic Super-Resolution from Non-isotropic 3D Electron Microscopy
The most sophisticated existing methods to generate 3D isotropic super-resolution (SR) from non-isotropic electron microscopy (EM) are based on...
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Deep Convolutional Neural Networks Based Framework for Estimation of Stomata Density and Structure from Microscopic Images
Analysis of stomata density and its configuration based on scanning electron microscopic (SEM) image of a leaf surface, is an effective way to...
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In-memory computing with emerging nonvolatile memory devices
The von Neumann bottleneck and memory wall have posed fundamental limitations in latency and energy consumption of modern computers based on von...
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Information Processing and Storage in the Brain
This chapter aims to illustrate the reception, encoding, and storage of information—including its modification through learning—in the brain of...
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Factors influencing the adoption of computerized medical diagnosing system for tuberculosis
The study of the factors that influence the use of automated diagnosing system for Tuberculosis (TB) can help in develo** a strategy to enhance...
