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Fetal Cortex Segmentation with Topology and Thickness Loss Constraints
The segmentation of the fetal cerebral cortex from magnetic resonance imaging (MRI) is an important tool for neurobiological research about the...
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A contour perception model that simulates the complex connection pattern of the visual cortex
Contour detection is the basic content of image processing and plays an important role in image analysis and target recognition. This paper proposed...
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Deep Labeling of fMRI Brain Networks Using Cloud Based Processing
Resting state fMRI is an imaging modality which reveals brain activity localization through signal changes, in what is known as Resting State...
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A Gray Code model for the encoding of grid cells in the Entorhinal Cortex
In the brains of humans and mammals, the formation of episodic memories results from the association between objects, space and time. Both the...
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Single-Trace Clustering Power Analysis of the Point-Swap** Procedure in the Three Point Ladder of Cortex-M4 SIKE
In this paper, the recommended implementation of the post-quantum key exchange SIKE for Cortex-M4 is attacked through power analysis with a single...
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Weakly Supervised Cerebellar Cortical Surface Parcellation with Self-Visual Representation Learning
The cerebellum (i.e., little brain) plays an important role in motion and balances control abilities, despite its much smaller size and deeper sulci...
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Extremely Weakly-Supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation
Accurate analysis and modeling of renal functions require a precise segmentation of the renal blood vessels. Micro-CT scans provide image data at...
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A High-Resolution Model of the Human Entorhinal Cortex in the ‘BigBrain’ – Use Case for Machine Learning and 3D Analyses
The ‘BigBrain’ is a high-resolution data set of the human brain that enables three-dimensional (3D) analyses with a 20 µm spatial resolution at...
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Automatic Food Labels Reading System
Growing obesity has been a worldwide issue for several years. This is the outcome of common nutritional disorders which results in obese individuals...
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Cell Counting with Inverse Distance Kernel and Self-supervised Learning
We present a solution to image-based cell counting with dot annotations for both 2D and 3D cases. Current approaches have two major limitations: 1)...
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Yoga Practitioners and Non-yoga Practitioners to Deal Neurodegenerative Disease in Neuro Regions
The ultimate goal of the research study is to determine if regular practice of yoga has any beneficial effects on brain functions and...
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A DNN-Based Learning Framework for Continuous Movements Segmentation
This study presents a novel experimental paradigm for collecting Electromyography (EMG) data from continuous movement sequences and a Deep Neural...
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Side-Channel Analysis for the Re-Keying Protocol of Bluetooth Low Energy
In the era of the Internet of Things, Bluetooth low energy (BLE/BTLE) plays an important role as a well-known wireless communication technology....
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Brain MRI to PET Synthesis and Amyloid Estimation in Alzheimer’s Disease via 3D Multimodal Contrastive GAN
Positron emission tomography (PET) can detect brain amyloid-β (Aβ) deposits, a diagnostic hallmark of Alzheimer’s disease and a target for disease...
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Connecto-informatics at the mesoscale: current advances in image processing and analysis for map** the brain connectivity
Map** neural connections within the brain has been a fundamental goal in neuroscience to understand better its functions and changes that follow...
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Modeling Hierarchical Architectures with Genetic Programming and Neuroscience Knowledge for Image Classification Through Inferential Knowledge
Brain programming is a methodology based on the idea that templates are necessary to describe artificial dorsal and ventral streams and their...
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The Open Kidney Ultrasound Data Set
Ultrasound is widely used and affordable diagnostic tool for medical imaging. With the increasing popularity of machine learning, ultrasound research...
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Web-S4AE: a semi-supervised stacked sparse autoencoder model for web robot detection
Web robots are automated computer programs that can be exploited for benign and malicious activities such as website indexing, monitoring, or...
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Improving Traffic Sign Recognition by Active Search
We describe an iterative active-learning algorithm to recognise rare traffic signs. A standard ResNet is trained on a training set containing only a...
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Bridging the Gap in ECG Classification: Integrating Self-supervised Learning with Human-in-the-Loop Amid Medical Equipment Hardware Constraints
Arrhythmia, a cardiac condition, is frequently diagnosed by classifying heartbeats using electrocardiograms (ECG). This classification is a crucial...