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A deep learning based cognitive model to probe the relation between psychophysics and electrophysiology of flicker stimulus
The flicker stimulus is a visual stimulus of intermittent illumination. A flicker stimulus can appear flickering or steady to a human subject,...
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Evaluative Item-Contrastive Explanations in Rankings
The remarkable success of Artificial Intelligence in advancing automated decision-making is evident both in academia and industry. Within the...
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Improving Likert scale big data analysis in psychometric health economics: reliability of the new compositional data approach
Bipolar psychometric scales data are widely used in psychologic healthcare. Adequate psychological profiling benefits patients and saves time and...
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Multidimensional graph transformer networks for trajectory prediction in urban road intersections
With the rapid development of autonomous driving, accurately predicting the future movement trajectories of various agents in complex scenarios, such...
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Granular Syntax Processing with Multi-Task and Curriculum Learning
Syntactic processing techniques are the foundation of natural language processing (NLP), supporting many downstream NLP tasks. In this paper, we...
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Twin Bounded Support Vector Machine with Capped Pinball Loss
In order to obtain a more robust and sparse classifier, in this paper, we propose a novel classifier termed as twin bounded support vector machine...
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Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-varying high gain-based...
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Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey
Over the past few years, larger and deeper neural network models, particularly convolutional neural networks (CNNs), have consistently advanced...
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Unmasking GAN-Generated Faces with Optimal Deep Learning and Cognitive Computing-Based Cutting-Edge Detection System
The emergence of deep learning (DL) has improved the excellence of generated media. However, with the enlarged level of photorealism, synthetic media...
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A survey of multi-population optimization algorithms for tracking the moving optimum in dynamic environments
The solution spaces of many real-world optimization problems change over time. Such problems are called dynamic optimization problems (DOPs), which...
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Cognitive Intelligent Decisions for Big Data and Cloud Computing in Industrial Applications using Trifold Algorithms
In contemporary real-time applications, diminutive devices are increasingly employing a greater portion of the spectrum to transmit data despite the...
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Learning from Failure: Towards Develo** a Disease Diagnosis Assistant That Also Learns from Unsuccessful Diagnoses
In recent years, automatic disease diagnosis has gained immense popularity in research and industry communities. Humans learn a task through both...
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Multi-Modal Generative DeepFake Detection via Visual-Language Pretraining with Gate Fusion for Cognitive Computation
With the widespread adoption of deep learning, there has been a notable increase in the prevalence of multimodal deepfake content. These deepfakes...
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Towards Long-Term Remembering in Federated Continual Learning
BackgroundFederated Continual Learning (FCL) involves learning from distributed data on edge devices with incremental knowledge. However, current FCL...
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Prognostic prediction model for esophageal cancer based on probability membrane systems
Esophageal squamous cell carcinoma (ESCC) is a clinically common heterogeneous malignant tumor of the digestive system and also one of the diseases...
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SPEI-FL: Serverless Privacy Edge Intelligence-Enabled Federated Learning in Smart Healthcare Systems
Smart healthcare systems promise significant benefits for fast and accurate medical decisions. However, working with personal health data presents...
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Evolutionary spiking neural networks: a survey
Spiking neural networks (SNNs) are gaining increasing attention as potential computationally efficient alternatives to traditional artificial neural...
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Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective
The automatic analysis of histology images is an open research field where machine learning techniques and neural networks, especially deep...
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Cognitive Tracing Data Trails: Auditing Data Provenance in Discriminative Language Models Using Accumulated Discrepancy Score
The burgeoning practice of unauthorized acquisition and utilization of personal textual data (e.g., social media comments and search histories) by...
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Advancing Medical Imaging Through Generative Adversarial Networks: A Comprehensive Review and Future Prospects
In medical imaging, traditional methods have long been relied upon. However, the integration of Generative Adversarial Networks (GANs) has sparked a...
