AIMC Topic: Algorithms

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Research on partial discharge signal recognition and classification of power transformer based on acoustic-VMD and CNN-LSTM.

PloS one
Partial discharge (PD) detection in power transformers is critical for preventing insulation failures in modern power grids, yet remains challenging due to signal complexity and environmental noise. Existing methods struggle with accurate PD classifi...

Neuromorphic computing paradigms enhance robustness through spiking neural networks.

Nature communications
The success of deep learning methods over the past decade has been partially shrouded in the shadow of adversarial attacks. Even a tiny undetectable deformation can lead to vicious misleading targeted at safety-critical applications. In contrast, the...

Deep domain adaptation eliminates costly data required for task-agnostic wearable robotic control.

Science robotics
Data-driven methods have transformed our ability to assess and respond to human movement with wearable robots, promising real-world rehabilitation and augmentation benefits. However, the proliferation of data-driven methods, with the associated deman...

Automated thyroid nodule classification in ultrasound imaging using a hybrid vision transformer and Wasserstein GAN with gradient penalty.

Scientific reports
In this study, we present a novel hybrid model combining the Vision Transformer (ViT) and Wasserstein Generative Adversarial Networks with Gradient Penalty (WGAN-GP) for thyroid nodule detection in ultrasound images. While traditional methods, such a...

Fusion of classical and deep learning features with incremental learning for improved classification of lung and colon cancer.

Scientific reports
Correct histopathological image classification of lung and colon cancer is a stringent challenge for clinical pathology. This work introduces a hybrid deep learning network by combining traditional handcrafted features of LBP, GLCM, wavelet, color, a...

Construction and validation of a risk prediction model for complications in patients with acute leukemia based on machine learning.

Scientific reports
Early-phase severe complications remain a major cause of morbidity and mortality during induction chemotherapy for acute leukaemia. Existing risk scores capture only limited prognostic variance and are rarely well-calibrated for clinical decision sup...

An intelligent taekwondo coaching system based on augmented reality technology with real-time feedback mechanisms.

Scientific reports
Traditional taekwondo training methods face limitations in providing objective, real-time feedback for technique improvement, relying primarily on subjective instructor observations that may lack precision and consistency. This research presents an i...

Explainable and likelihood aware AI framework for MRI-based pixel-level bladder tumour prediction.

Scientific reports
Bladder tumours (BTs) pose significant clinical challenges due to their high recurrence rates and risk of progression to invasive malignancies, which emphasises the need for early and accurate detection. Magnetic resonance imaging (MRI), with its sup...

Detection of violence in football sport based on deep learning and optimization algorithm.

Scientific reports
Among the various sports activities that are carried out all over the world, football is undoubtedly the most popular, most participated in and most watched activity and sport. The increasing spread of sports has caused it to break down geographical,...

Cross-platform multi-cancer histopathology classification using local-window vision transformers.

Scientific reports
Cancer remains one of the leading causes of global mortality, with lung, colon, skin, and breast cancers contributing significantly to the disease burden. Accurate and timely classification of histopathological images is critical for effective diagno...