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Found 16 papers, 2 papers with code
Generating Visual Stimuli from EEG Recordings using Transformer-encoder based EEG encoder and GAN
In this study, we tackle a modern research challenge within the field of perceptual brain decoding, which revolves around synthesizing images from EEG signals using an adversarial deep learning framework.
Classification of attention performance post-longitudinal tDCS via functional connectivity and machine learning methods
From Day 2 through Day 8, the experimental group was administered 1mA tDCS, while the control group received sham tDCS.
Prediction of multitasking performance post-longitudinal tDCS via EEG-based functional connectivity and machine learning methods
From Day 2 to Day 7, subjects in the experimental condition undertook 15 minutes of 2mA anodal tDCS stimulation during task training.
Image Forgery Detection with Interpretability
We consider the detection of both copy-move forgeries and inpainting based forgeries.
Stain Normalized Breast Histopathology Image Recognition using Convolutional Neural Networks for Cancer Detection
Further, we evaluated the performance and efficiency of popular lightweight networks using stain normalized images and found that EfficientNet outperforms VGG16 and MobileNet in terms of test accuracy and F1 Score.
MHATC: Autism Spectrum Disorder identification utilizing multi-head attention encoder along with temporal consolidation modules
Resting-state fMRI is commonly used for diagnosing Autism Spectrum Disorder (ASD) by using network-based functional connectivity.
Virtual Screening of Pharmaceutical Compounds with hERG Inhibitory Activity (Cardiotoxicity) using Ensemble Learning
In silico prediction of cardiotoxicity with high sensitivity and specificity for potential drug molecules can be of immense value.
Semantic Features Aided Multi-Scale Reconstruction of Inter-Modality Magnetic Resonance Images
Long acquisition time (AQT) due to series acquisition of multi-modality MR images (especially T2 weighted images (T2WI) with longer AQT), though beneficial for disease diagnosis, is practically undesirable.
Detecting Deepfakes with Metric Learning
With the arrival of several face-swapping applications such as FaceApp, SnapChat, MixBooth, FaceBlender and many more, the authenticity of digital media content is hanging on a very loose thread.
Copy-Move Forgery Classification via Unsupervised Domain Adaptation
In the current era, image manipulation is becoming increasingly easier, yielding more natural looking images, owing to the modern tools in image processing and computer vision techniques.
Role of Class-specific Features in Various Classification Frameworks for Human Epithelial (HEp-2) Cell Images
We believe that defining features with a good visual interpretation, is indeed important in a scenario, where such an approach is used in an interactive CAD system for pathologists.
Considerations for a PAP Smear Image Analysis System with CNN Features
Therefore, the primary step for automated screening can be cell-nuclei detection followed by segmentation of nuclei in the resulting single cell PAP-smear images.
Classifying Object Manipulation Actions based on Grasp-types and Motion-Constraints
Due to the variations in geometrical and motion constraints, there are different manipulations actions possible to perform different sets of actions with an object.
Learning to Decode 7T-like MR Image Reconstruction from 3T MR Images
Increasing demand for high field magnetic resonance (MR) scanner indicates the need for high-quality MR images for accurate medical diagnosis.
Siamese LSTM based Fiber Structural Similarity Network (FS2Net) for Rotation Invariant Brain Tractography Segmentation
In this paper, we propose a novel deep learning architecture combining stacked Bi-directional LSTM and LSTMs with the Siamese network architecture for segmentation of brain fibers, obtained from tractography data, into anatomically meaningful clusters.
Shape Estimation from Defocus Cue for Microscopy Images via Belief Propagation
Even with such an assumption, the ability of BP to provide good quality solutions while using non-convex priors, reflects in yielding plausible shape estimates in presence of fine structures on the objects under microscopy imaging.
