AIMC Topic: Algorithms

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DSSA-TCN: Exploiting adaptive sparse attention and diffusion graph convolutions in temporal convolutional networks for traffic flow forecasting.

PloS one
Accurate traffic flow forecasting is essential for intelligent transportation systems, yet the nonlinear and dynamically evolving spatio-temporal dependencies in urban road networks make reliable prediction challenging. Existing graph-based and atten...

A visual question answering method based on task decomposition.

PloS one
Visual question answering (VQA) as an interdisciplinary task of computer vision and natural language processing, estimating the model's visual reasoning ability, which requires the integration of image information extraction technology and natural la...

CattleNet-XAI: An explainable CNN framework for efficient cattle weight estimation.

PloS one
Accurate estimation of cattle weight is essential for effective farm management, health assessment, and productivity optimization. Traditional manual methods for weight estimation, however, are labor-intensive, time-consuming, and prone to inaccuraci...

Improving detection accuracy of heterogeneity in biological tissues through the combination of modulation-demodulation frame accumulation techniques and enhanced vgg16.

PloS one
Light source has obvious absorption and scattering effects during the transmission process of biological tissues, making it difficult to identify heterogeneities in multi-spectral images. This paper achieves a gradual improvement in the classificatio...

Homogeneous multi-antibiotics residual identification in various actual water via SERS spectra multilayer perceptron algorithm combined with Gaussian kernel density estimation data augmentation.

Analytica chimica acta
BACKGROUND: Antibiotic residues pose varying degrees of potential hazards to the water environment and human health due to their diverse types. Surface-enhanced Raman spectroscopy (SERS) technology can achieve rapid detection of various antibiotic re...

Nonenhanced CT-Based radiomics model enhances PTC detection in Hashimoto's thyroiditis.

BMC cancer
BACKGROUND: Hashimoto's thyroiditis (HT) is a common benign thyroid disease that often coexists with papillary thyroid carcinoma (PTC). Owing to the diffuse changes in the thyroid caused by HT, PTCs can be challenging to detect using conventional ima...

Predictive modeling of flavonoid efficacy against esophageal carcinoma: a comprehensive approach.

Scientific reports
Esophageal carcinoma poses a significant health challenge, particularly due to its notably high prevalence in East Asia, which underscores the urgent need for innovative treatment strategies. Natural flavonoids are polyphenolic compounds with signifi...

Refining cancer prediction with DNA sequencing and combined machine learning approaches.

Scientific reports
A high-accuracy DNA-based cancer risk predictor was developed by blending Logistic Regression with Gaussian Naive Bayes, and its hyperparameters were optimized via grid search. Five cancer types (BRCA1, KIRC, COAD, LUAD, PRAD) were classified in a co...

An enhanced deep learning-based framework for diagnosing apple leaf diseases.

Scientific reports
Timely and correct identification of diseases in the apple leaf is also important in protecting crop production and sustaining agriculture. This paper introduces E-YOLOv8, a lightweight improved version of YOLOv8, that can be implemented in real-time...

Multi-stage variational autoencoders for hierarchical molecular generation and activity optimization.

Journal of computer-aided molecular design
Deep generative models may detect novel compounds with favourable features, exhibiting chemical design potential. Traditional single-stage variational autoencoders (VAEs) lack validity, uniqueness, and biologically meaningful distribution alignment. ...