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Found 15 papers, 3 papers with code
BioNeRF: Biologically Plausible Neural Radiance Fields for View Synthesis
This paper presents BioNeRF, a biologically plausible architecture that models scenes in a 3D representation and synthesizes new views through radiance fields.
Enhancing Hyper-To-Real Space Projections Through Euclidean Norm Meta-Heuristic Optimization
The continuous computational power growth in the last decades has made solving several optimization problems significant to humankind a tractable task; however, tackling some of them remains a challenge due to the overwhelming amount of candidate solutions to be evaluated, even by using sophisticated algorithms.
DDIPNet and DDIPNet+: Discriminant Deep Image Prior Networks for Remote Sensing Image Classification
Research on remote sensing image classification significantly impacts essential human routine tasks such as urban planning and agriculture.
FEMa-FS: Finite Element Machines for Feature Selection
Identifying anomalies has become one of the primary strategies towards security and protection procedures in computer networks.
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks
In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities.
ComplexWoundDB: A Database for Automatic Complex Wound Tissue Categorization
Complex wounds usually face partial or total loss of skin thickness, healing by secondary intention.
Multimodal Speech Enhancement Using Burst Propagation
This paper proposes the MBURST, a novel multimodal solution for audio-visual speech enhancements that consider the most recent neurological discoveries regarding pyramidal cells of the prefrontal cortex and other brain regions.
Canonical Cortical Graph Neural Networks and its Application for Speech Enhancement in Audio-Visual Hearing Aids
Despite the recent success of machine learning algorithms, most models face drawbacks when considering more complex tasks requiring interaction between different sources, such as multimodal input data and logical time sequences.
A Novel Approach for Optimum-Path Forest Classification Using Fuzzy Logic
In the past decades, fuzzy logic has played an essential role in many research areas.
Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization
We employed the STARE dataset for external validation, ensuring a comprehensive assessment of the proposed approach.
MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional Neural Networks
In the last decade, exponential data growth supplied the machine learning-based algorithms' capacity and enabled their usage in daily life activities.
A Review of Deep Learning-based Approaches for Deepfake Content Detection
Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos.
Gait Recognition Based on Deep Learning: A Survey
In general, biometry-based control systems may not rely on individual expected behavior or cooperation to operate appropriately.
A Layer-Wise Information Reinforcement Approach to Improve Learning in Deep Belief Networks
With the advent of deep learning, the number of works proposing new methods or improving existent ones has grown exponentially in the last years.
Intestinal Parasites Classification Using Deep Belief Networks
Currently, approximately $4$ billion people are infected by intestinal parasites worldwide.
