Deep learning has been successfully used for tasks in the 2D image *** on 3D computer vision and deep geometry learning has also attracted *** achievements have been made regarding feature extraction and discriminatio...
详细信息
Deep learning has been successfully used for tasks in the 2D image *** on 3D computer vision and deep geometry learning has also attracted *** achievements have been made regarding feature extraction and discrimination of 3D *** recent advances in deep generative models such as generative adversarial networks,effective generation of 3D shapes has become an active research *** 2D images with a regular grid structure,3D shapes have various representations,such as voxels,point clouds,meshes,and implicit *** deep learning of 3D shapes,shape representation has to be taken into account as there is no unified representation that can cover all tasks *** such as the representativeness of geometry and topology often largely affect the quality of the generated 3D *** this survey,we comprehensively review works on deep-learning-based 3D shape generation by classifying and discussing them in terms of the underlying shape representation and the architecture of the shape *** advantages and disadvantages of each class are further *** also consider the 3D shape datasets commonly used for shape ***,we present several potential research directions that hopefully can inspire future works on this topic.
Alzheimer’s disease(AD)is a significant challenge in modern healthcare,with early detection and accurate staging remaining critical priorities for effective *** Deep Learning(DL)approaches have shown promise in AD di...
详细信息
Alzheimer’s disease(AD)is a significant challenge in modern healthcare,with early detection and accurate staging remaining critical priorities for effective *** Deep Learning(DL)approaches have shown promise in AD diagnosis,existing methods often struggle with the issues of precision,interpretability,and class *** study presents a novel framework that integrates DL with several eXplainable Artificial Intelligence(XAI)techniques,in particular attention mechanisms,Gradient-Weighted Class Activation Mapping(Grad-CAM),and Local Interpretable Model-Agnostic Explanations(LIME),to improve bothmodel interpretability and feature *** study evaluates four different DL architectures(ResMLP,VGG16,Xception,and Convolutional Neural Network(CNN)with attention mechanism)on a balanced dataset of 3714 MRI brain scans from patients aged 70 and *** proposed CNN with attention model achieved superior performance,demonstrating 99.18%accuracy on the primary dataset and 96.64% accuracy on the ADNI dataset,significantly advancing the state-of-the-art in AD *** ability of the framework to provide comprehensive,interpretable results through multiple visualization techniques while maintaining high classification accuracy represents a significant advancement in the computational diagnosis of AD,potentially enabling more accurate and earlier intervention in clinical settings.
The most prevalent cancer around the world is Skin cancer (SC). Clinical assessment of skin lesions is essential to evaluate the features of the disease;but it is limited by the variety of interpretations and long tim...
详细信息
One of the key challenges in e-commerce is how to provide relevant and personalized product recommendations to users. To achieve this, data analysis and text processing techniques are essential. This research aims to ...
详细信息
Meta-heuristic optimization algorithms have become widely used due to their outstanding features, such as gradient-free mechanisms, high flexibility, and great potential for avoiding local optimal solutions. This rese...
详细信息
Maintaining a regular daily activity routine is essential for overall health and well-being. Wearable sensors offer a convenient way to track daily activities, but accurately identifying a wide range of activities rem...
详细信息
NoSQL database has gained popularity in Big Data and other various applications for its simplicity and flexibility. The non-relational nature of NoSQL database such as MongoDB proves to improve development lifecycles ...
详细信息
The Internet of Things(IoT)has taken the interconnected world by *** to their immense applicability,IoT devices are being scaled at exponential proportions ***,very little focus has been given to securing such *** the...
详细信息
The Internet of Things(IoT)has taken the interconnected world by *** to their immense applicability,IoT devices are being scaled at exponential proportions ***,very little focus has been given to securing such *** these devices are constrained in numerous aspects,it leaves network designers and administrators with no choice but to deploy them with minimal or no security at *** have seen distributed denial-ofservice attacks being raised using such devices during the infamous Mirai botnet attack in *** we propose a lightweight authentication protocol to provide proper access to such *** have considered several aspects while designing our authentication protocol,such as scalability,movement,user registration,device registration,*** define the architecture we used a three-layered model consisting of cloud,fog,and edge *** have also proposed several pre-existing cipher suites based on post-quantum cryptography for evaluation and *** also provide a fail-safe mechanism for a situation where an authenticating server might fail,and the deployed IoT devices can self-organize to keep providing services with no human *** find that our protocol works the fastest when using ring learning with *** prove the safety of our authentication protocol using the automated validation of Internet security protocols and applications *** conclusion,we propose a safe,hybrid,and fast authentication protocol for authenticating IoT devices in a fog computing environment.
Malaria is an endemic in various tropical countries. The gold standard for disease detection is to examine the blood smears of patients by an expert medical professional to detect malaria parasite called Plasmodium. I...
详细信息
This paper proposed a model based on bidirectional Long Short-Term Memory (Bi-LSTM) and Bayesian optimization to detect different drones in different Scenarios. Six different drones in three distinct scenarios—cloudy...
详细信息
暂无评论