AIMC Topic: Learning

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Training Novel Adaptive Fuzzy Cognitive Map by Knowledge-Guidance Learning Mechanism for Large-Scale Time-Series Forecasting.

IEEE transactions on cybernetics
A fuzzy cognitive map (FCM) is a graph-based knowledge representation model wherein the connections of the nodes (edges) represent casual relationships between the knowledge items associated with the nodes. This model has been applied to solve variou...

Learning Performance of Weighted Distributed Learning With Support Vector Machines.

IEEE transactions on cybernetics
The divide-and-conquer strategy is a very effective method of dealing with big data. Noisy samples in big data usually have a great impact on algorithmic performance. In this article, we introduce Markov sampling and different weights for distributed...

FrMLNet: Framelet-Based Multilevel Network for Pansharpening.

IEEE transactions on cybernetics
Most modern satellites can provide two types of images: 1) panchromatic (PAN) image and 2) multispectral (MS) image. The former has high spatial resolution and low spectral resolution, while the latter has high spectral resolution and low spatial res...

Fixed-Time Recurrent NN Learning Control of Uncertain Robotic Manipulators with Time-Varying Constraints: Experimental Verification.

Sensors (Basel, Switzerland)
This paper proposes a learning control framework for the robotic manipulator's dynamic tracking task demanding fixed-time convergence and constrained output. In contrast with model-dependent methods, the proposed solution deals with unknown manipulat...

Transformer-Based Approach Via Contrastive Learning for Zero-Shot Detection.

International journal of neural systems
Zero-shot detection (ZSD) aims to locate and classify unseen objects in pictures or videos by semantic auxiliary information without additional training examples. Most of the existing ZSD methods are based on two-stage models, which achieve the detec...

Extreme image transformations affect humans and machines differently.

Biological cybernetics
Some recent artificial neural networks (ANNs) claim to model aspects of primate neural and human performance data. Their success in object recognition is, however, dependent on exploiting low-level features for solving visual tasks in a way that huma...

An equitable and sustainable community of practice framework to address the use of artificial intelligence for global health workforce training.

Human resources for health
Artificial Intelligence (AI) technologies and data science models may hold potential for enabling an understanding of global health inequities and support decision-making related toward possible interventions. However, AI inputs should not perpetuate...

Canonical circuit computations for computer vision.

Biological cybernetics
Advanced computer vision mechanisms have been inspired by neuroscientific findings. However, with the focus on improving benchmark achievements, technical solutions have been shaped by application and engineering constraints. This includes the traini...

MedKPL: A heterogeneous knowledge enhanced prompt learning framework for transferable diagnosis.

Journal of biomedical informatics
Artificial Intelligence (AI) based diagnosis systems have emerged as powerful tools to reform traditional medical care. Each clinician now wants to have his own intelligent diagnostic partner to expand the range of services he can provide. However, t...

Ergonomic investigations on novel dynamic postural estimator using blaze pose and transfer learning.

Ergonomics
The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using 'BlazePose' with a data set of 50,00...