Academic Articles & Research Papers

A Deep Learning Harmonization of Multi-Vendor MRI for Robust Intervertebral Disc Segmentation

Magnetic resonance imaging (MRI) provides enhanced soft tissue contrast and high spatial resolution. However, the relationship between intensity values among soft tissues in MRI is inconsistent, even when obtained under the same conditions ...

Using an Inspired Quantum-Classical Sequential Neural Network to Segment Liver Tumor Images Accurately

Medical analytics based on multimodal intelligence are essential to contemporary healthcare, especially in the diagnosis and detection of liver cancer. However, low contrast, varied textures, and irregular tumor forms in medical imaging con...

Pointwise Convolutional Neural Networks

Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently. However, the capability of using point clouds with convolutional neural network has been so far not fully explored....

Artificial neural networks for speech and vision

Neural Networks for speech processing. Neural Networks in the acquisition of speech by machine. The nervous system - fantasy and reality. Processing of complex stimuli in the mammalian cochlear nucleus. On the possible role of auditory peri...

Progress in neural networks

Receptive field calculus, Jan J. Koenderink visual reconstruction and data fusion, D. Suter visual perception of translational and rotational motion, Jim-Shih Liaw, Irwin K. King and Michael A. Arbib neural network for recovering observer m...

Slimmable Neural Networks

We present a simple and general method to train a single neural network executable at different widths (number of channels in a layer), permitting instant and adaptive accuracy-efficiency trade-offs at runtime. Instead of training individua...

Fuzzy logic and neural network handbook

Fuzzy logic principles and algorithms design guidelines for fuzzy logic systems enhanced training algorithms maximum likelihood training temporal difference learning NADINE hybrid learning systems explanation and reasoning within connectivi...

Neural Network for Pattern Recognition

As famously quoted by Margaret Heffernan: - “A great deal of creativity is about pattern recognition, and what you need to discern patterns is tons of data. Your mind collects that data by taking note of random details and anomalies easily ...

FCM Clustering Algorithms for Segmentation of Brain MR Images

The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR) brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main t...

Statistical testing of agreement in overlap-based performance between an AI segmentation device and a multi-expert human panel without requiring a reference standard.

Hardware-Anchored ES-SPA: A Dynamic Zero-Trust Architecture for Secure eSIM Provisioning in 6G IoT via Moving Target Defense

The rapid evolution of 6G networks and large-scale Internet of Things (IoT) deployments intensifies security and privacy challenges in embedded SIM (eSIM) Remote SIM Provisioning (RSP), particularly during the bootstrap and profile delivery...

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

Sequential region labelling, also known as connected components labelling, is a standard image segmentation problem that joins contiguous foreground pixels into blobs. Despite its long development history and widespread use across diverse d...

Seeing and Thinking about Urban Blue–Green Space: Monitoring Public Landscape Preferences Using Bimodal Data

Urban blue–green spaces (UBGSs) are a significant avenue for addressing the worldwide mental health crisis. To effectively optimise landscape design and management for the promotion of health benefits from UBGS, it is crucial to objectively...

Large Language Models and 3D Vision for Intelligent Robotic Perception and Autonomy

With the rapid advancement of artificial intelligence and robotics, the integration of Large Language Models (LLMs) with 3D vision is emerging as a transformative approach to enhancing robotic sensing technologies. This convergence enables ...

Handbook of Natural Language Processing

Symbolic approaches to natural language processing tokenisation and sentence segmentation lexical analysis parsing techniques semantic analysis discourse structure and intention recognition natural language generation intelligent writing as...

TexTNet: a texture-guided hierarchical architecture for prostate cancer Gleason segmentation in whole slide images.

Identification of camouflage military individuals with deep learning approaches DFAN and SINETV2

Abstract Camouflaged object detection particularly is considered as challenging and crucial because these objects are designed to either mimic their environment or be completely hidden within it. The goal of camouflage patterns utilization ...

Computer Vision

Abstract: Computer vision is a field of artificial intelligence that focuses on enabling computers to understand and interpret visual information from images or videos. It involves developing algorithms and techniques to extract meaningful ...

Transformer in Computer Vision

Transformer is widely used in Natural Language Processing (NLP), in which numerous papers have been proposed. Recently, the transformer has been borrowed for many computer vision tasks. However, there are few papers to give a comprehensive ...

Robotic Template Library

Robotic Template Library (RTL) is a set of tools for dealing with geometry and point cloud processing, especially in robotic applications. The software package covers basic objects such as vectors, line segments, quaternions, rigid transfor...