AIMC Topic: Neural Networks, Computer

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XLLC-Net: A lightweight and explainable CNN for accurate lung cancer classification using histopathological images.

PloS one
Lung cancer imaging plays a crucial role in early diagnosis and treatment, where machine learning and deep learning have significantly advanced the accuracy and efficiency of disease classification. This study introduces the Explainable and Lightweig...

GDFGAT: Graph attention network based on feature difference weight assignment for telecom fraud detection.

PloS one
In recent years, the number of telecom frauds has increased significantly, causing substantial losses to people's daily lives. With technological advancements, telecom fraud methods have also become more sophisticated, making fraudsters harder to det...

DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation.

PloS one
Medical image segmentation plays a crucial role in computer-aided diagnosis. By segmenting pathological tissues in medical images, doctors can observe anatomical structures more clearly, thereby achieving more accurate disease diagnoses. However, exi...

TransembleNet: Enhancing vector mosquito species classification through transfer learning-based ensemble model.

PloS one
Mosquitoes, which belong to diverse species, play a significant role in ecological systems and public health. The accurate identification (classification) of mosquito species is essential for a comprehensive understanding of their ecological roles, b...

A deep learning-based algorithm for the detection of personal protective equipment.

PloS one
Personal protective equipment (PPE) is critical for ensuring the safety of construction workers. However, site surveillance images from construction sites often feature multi-size and multi-scale targets, leading to low detection accuracy for PPE in ...

Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM.

PloS one
Artificial Intelligence (AI) is being integrated into increasingly more domains of everyday activities. Whereas AI has countless benefits, its convoluted and sometimes vague internal operations can establish difficulties. Nowadays, AI is significantl...

T-RippleGNN: Predicting traffic flow through ripple propagation with attentive graph neural networks.

PloS one
Recently, accurate traffic flow prediction has become a significant part of intelligent transportation systems, which can not only satisfy citizens' travel need and life satisfaction, but also benefit urban traffic management and control. However, tr...

Asymptotic expansions as control variates for deep solvers to fully-coupled forward-backward stochastic differential equations.

PloS one
Coupled forward-backward stochastic differential equations (FBSDEs) are closely related to financially important issues such as optimal investment. However, it is well known that obtaining solutions is challenging, even when employing numerical metho...

Innovative novel regularized memory graph attention capsule network for financial fraud detection.

PloS one
Financial fraud detection (FFD) is crucial for ensuring the safety and efficiency of financial transactions. This article presents the Regularised Memory Graph Attention Capsule Network (RMGACNet), an original architecture aiming at improving fraud d...

Multi-convolutional neural networks for cotton disease detection using synergistic deep learning paradigm.

PloS one
Cotton is a major cash crop, and increasing its production is extremely important worldwide, especially in agriculture-led economies. The crop is susceptible to various diseases, leading to decreased yields. In recent years, advancements in deep lear...