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Found 21 papers, 5 papers with code
Knowledge-Based Convolutional Neural Network for the Simulation and Prediction of Two-Phase Darcy Flows
Physics-informed neural networks (PINNs) have gained significant prominence as a powerful tool in the field of scientific computing and simulations.
Harnessing the Power of Large Vision Language Models for Synthetic Image Detection
This study contributes to the advancement of synthetic image detection by exploiting the capabilities of visual language models such as BLIP-2 and ViTGPT2.
Bi-LORA: A Vision-Language Approach for Synthetic Image Detection
Advancements in deep image synthesis techniques, such as generative adversarial networks (GANs) and diffusion models (DMs), have ushered in an era of generating highly realistic images.
Face to Cartoon Incremental Super-Resolution using Knowledge Distillation
Facial super-resolution/hallucination is an important area of research that seeks to enhance low-resolution facial images for a variety of applications.
When Geoscience Meets Generative AI and Large Language Models: Foundations, Trends, and Future Challenges
Generative Artificial Intelligence (GAI) represents an emerging field that promises the creation of synthetic data and outputs in different modalities.
Pain Analysis using Adaptive Hierarchical Spatiotemporal Dynamic Imaging
These representations are optimized for two tasks: estimating pain intensity and differentiating between genuine and simulated pain expressions.
Skew Probabilistic Neural Networks for Learning from Imbalanced Data
This paper introduces an imbalanced data-oriented approach using probabilistic neural networks (PNNs) with a skew normal probability kernel to address this major challenge.
Evaluation of Pre-Trained CNN Models for Geographic Fake Image Detection
Thanks to the remarkable advances in generative adversarial networks (GANs), it is becoming increasingly easy to generate/manipulate images.
Knowledge-based Deep Learning for Modeling Chaotic Systems
Our proposed KDL can learn the complex patterns governing chaotic systems by jointly training on real and simulated data directly from the dynamics and their differential equations.
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series Forecasting
Deep learning utilizing transformers has recently achieved a lot of success in many vital areas such as natural language processing, computer vision, anomaly detection, and recommendation systems, among many others.
Probabilistic AutoRegressive Neural Networks for Accurate Long-range Forecasting
In this study, we introduce the Probabilistic AutoRegressive Neural Networks (PARNN), capable of handling complex time series data exhibiting non-stationarity, nonlinearity, non-seasonality, long-range dependence, and chaotic patterns.
Multi-view Deep Features for Robust Facial Kinship Verification
We refer that we used the SSC method in RFIW'20 competition using the eight deep features concatenation.
Clinical Depression and Affect Recognition with EmoAudioNet
Automatic analysis of emotions and affects from speech is an inherently challenging problem with a broad range of applications in Human-Computer Interaction (HCI), health informatics, assistive technologies and multimedia retrieval.
Human-Computer Interaction Sound Audio and Speech Processing
AVD: Adversarial Video Distillation
The key idea is to represent videos by compressing them in the form of realistic images, which can be used in a variety of video-based scene analysis applications.
Forensic shoe-print identification: a brief survey
As an advanced research topic in forensics science, automatic shoe-print identification has been extensively studied in the last two decades, since shoe marks are the clues most frequently left in a crime scene.
Deep Discriminative Model for Video Classification
This paper presents a new deep learning approach for video-based scene classification.
Deep Spatiotemporal Representation of the Face for Automatic Pain Intensity Estimation
Automatic pain intensity assessment has a high value in disease diagnosis applications.
Kinship Verification from Videos using Spatio-Temporal Texture Features and Deep Learning
Automatic kinship verification using facial images is a relatively new and challenging research problem in computer vision.
Unsupervised Deep Hashing for Large-scale Visual Search
Learning based hashing plays a pivotal role in large-scale visual search.
Facial age estimation using BSIF and LBP
Human face aging is irreversible process causing changes in human face characteristics such us hair whitening, muscles drop and wrinkles.
face anti-spoofing based on color texture analysis
Research on face spoofing detection has mainly been focused on analyzing the luminance of the face images, hence discarding the chrominance information which can be useful for discriminating fake faces from genuine ones.
Ranked #3 on
Face Anti-Spoofing
on MSU-MFSD
