AIMC Topic: Algorithms

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CATransU-Net: Cross-attention TransU-Net for field rice pest detection.

PloS one
Accurate detection of rice pests in field is a key problem in field pest control. U-Net can effectively extract local image features, and Transformer is good at dealing with long-distance dependencies. A Cross-Attention TransU-Net (CATransU-Net) mode...

rbpTransformer: A novel deep learning model for prediction of piRNA and mRNA bindings.

PloS one
An important issue in biotechnology is predicting whether a piRNA and an mRNA will or will not bind. Research and treatment of diseases, drug discovery, and the silencing and regulation of genes, transposons, and genomic stability may all benefit fro...

Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.

PloS one
Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-being of patients and develop customized therapeutic plans. Despite its importance, achieving precise forecasts remains a formidable challenge. To tackle...

A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks.

PloS one
This paper presents a novel framework for detecting and predicting abnormal traffic events on highways. Current traffic monitoring systems often rely on single data sources, which limits their detection accuracy and robustness in complex environments...

Edge computing based english translation model using fuzzy semantic optimal control technique.

PloS one
People's need for English translation is gradually growing in the modern era of technological advancements, and a computer that can comprehend and interpret English is now more crucial than ever. Some issues, including ambiguity in English translatio...

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

PloS one
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...

Construction of VAE-GRU-XGBoost intrusion detection model for network security.

PloS one
With the advent of the big data era, the threat of network security is becoming increasingly severe. In order to cope with complex network attacks and ensure network security, a network intrusion detection model is constructed relying on deep learnin...

PoseNet++: A multi-scale and optimized feature extraction network for high-precision human pose estimation.

PloS one
Human pose estimation (HPE) has made significant progress with deep learning; however, it still faces challenges in handling occlusions, complex poses, and complex multi-person scenarios. To address these issues, we propose PoseNet++, a novel approac...

Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data.

PloS one
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...

Application of IRSA-BP neural network in diagnosing diabetes.

PloS one
Within the healthcare sector, the application of machine learning is gaining prominence, notably enhancing the efficiency and precision of diagnostic procedures. This study focuses on this key area of diabetes prediction and aims to develop an innova...