AIMC Topic: Neural Networks, Computer

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YOLOv7-Branch: A Jujube Leaf Branch Detection Model for Agricultural Robot.

Sensors (Basel, Switzerland)
The intelligent harvesting technology for jujube leaf branches presents a novel avenue for enhancing both the quantity and quality of jujube leaf tea, whereas the precise detection technology for jujube leaf branches emerges as a pivotal factor const...

Prediction of leukemia peptides using convolutional neural network and protein compositions.

BMC cancer
Leukemia is a type of blood cell cancer that is in the bone marrow's blood-forming cells. Two types of Leukemia are acute and chronic; acute enhances fast and chronic growth gradually which are further classified into lymphocytic and myeloid leukemia...

Optimizing neural networks using spider monkey optimization algorithm for intrusion detection system.

Scientific reports
The constantly changing nature of cyber threats presents unprecedented difficulties for people, institutions, and governments across the globe. Cyber threats are a major concern in today's digital world like hacking, phishing, malware, and data breac...

Hybrid framework for membrane protein type prediction based on the PSSM.

Scientific reports
Membrane proteins are considered the major source of drug targets and are indispensable for drug design and disease prevention. However, traditional biomechanical experiments are costly and time-consuming; thus, many computational methods for predict...

Emergence and reconfiguration of modular structure for artificial neural networks during continual familiarity detection.

Science advances
Advances in artificial intelligence enable neural networks to learn a wide variety of tasks, yet our understanding of the learning dynamics of these networks remains limited. Here, we study the temporal dynamics during learning of Hebbian feedforward...

A deep learning-based method for the detection and segmentation of breast masses in ultrasound images.

Physics in medicine and biology
Automated detection and segmentation of breast masses in ultrasound images are critical for breast cancer diagnosis, but remain challenging due to limited image quality and complex breast tissues. This study aims to develop a deep learning-based meth...

Flexibility in conceptual combinations: A neural network model of gradable adjective modification.

PloS one
Our ability to combine simple constituents into more complex conceptual combinations is a fundamental aspect of cognition. Gradable adjectives (e.g., 'tall' and 'light') are a critical example of this process, as their meanings vary depending on the ...

MEFFNet: Forecasting Myoelectric Indices of Muscle Fatigue in Healthy and Post-Stroke During Voluntary and FES-Induced Dynamic Contractions.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Myoelectric indices forecasting is important for muscle fatigue monitoring in wearable technologies, adaptive control of assistive devices like exoskeletons and prostheses, functional electrical stimulation (FES)-based Neuroprostheses, and more. Non-...

BiRNN-DDI: A Drug-Drug Interaction Event Type Prediction Model Based on Bidirectional Recurrent Neural Network and Graph2Seq Representation.

Journal of computational biology : a journal of computational molecular cell biology
Research on drug-drug interaction (DDI) prediction, particularly in identifying DDI event types, is crucial for understanding adverse drug reactions and drug combinations. This work introduces a Bidirectional Recurrent Neural Network model for DDI ev...