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Found 15 papers, 3 papers with code
ReViT: Enhancing Vision Transformers with Attention Residual Connections for Visual Recognition
Vision Transformer (ViT) self-attention mechanism is characterized by feature collapse in deeper layers, resulting in the vanishing of low-level visual features.
Ranked #488 on
Image Classification
on ImageNet
Distilled Gradual Pruning with Pruned Fine-tuning
Neural Networks (NNs) have been driving machine learning progress in recent years, but their larger models present challenges in resource-limited environments.
Ranked #25 on
Image Classification
on CIFAR-10
(Top-1 Accuracy metric)
Medicinal Boxes Recognition on a Deep Transfer Learning Augmented Reality Mobile Application
Taking medicines is a fundamental aspect to cure illnesses.
Analyzing EEG Data with Machine and Deep Learning: A Benchmark
Nowadays, machine and deep learning techniques are widely used in different areas, ranging from economics to biology.
Human Silhouette and Skeleton Video Synthesis through Wi-Fi signals
The latter conditions signal-based features in the visual domain to completely replace visual data.
SIRe-Networks: Convolutional Neural Networks Architectural Extension for Information Preservation via Skip/Residual Connections and Interlaced Auto-Encoders
Improving existing neural network architectures can involve several design choices such as manipulating the loss functions, employing a diverse learning strategy, exploiting gradient evolution at training time, optimizing the network hyper-parameters, or increasing the architecture depth.
Study on Transfer Learning Capabilities for Pneumonia Classification in Chest-X-Rays Image
Over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of screening tools with high diagnostic accuracy for new illnesses such as COVID-19.
3D Hand Pose and Shape Estimation from RGB Images for Keypoint-Based Hand Gesture Recognition
Estimating the 3D pose of a hand from a 2D image is a well-studied problem and a requirement for several real-life applications such as virtual reality, augmented reality, and hand gesture recognition.
Ensemble CNN and Uncertainty Modeling to Improve Automatic Identification/Segmentation of Multiple Sclerosis Lesions in Magnetic Resonance Imaging
To date, several automated strategies for identification/segmentation of Multiple Sclerosis (MS) lesions with the use of Magnetic Resonance Imaging (MRI) have been presented, but they are outperformed by human experts, from whom they act very differently.
Convolutional Neural Networks for Automatic Detection of Artifacts from Independent Components Represented in Scalp Topographies of EEG Signals
Artifacts, due to eye movements and blink, muscular/cardiac activity and generic electrical disturbances, have to be recognized and eliminated to allow a correct interpretation of the useful brain signals (UBS) of EEG.
Multimodal Feature Fusion and Knowledge-Driven Learning via Experts Consult for Thyroid Nodule Classification
Computer-aided diagnosis (CAD) is becoming a prominent approach to assist clinicians spanning across multiple fields.
A Light CNN for detecting COVID-19 from CT scans of the chest
OVID-19 is a world-wide disease that has been declared as a pandemic by the World Health Organization.
Wi-Fi Passive Person Re-Identification based on Channel State Information
With the increasing need for wireless data transfer, Wi-Fi networks have rapidly grown in recent years providing high throughput and easy deployment.
Signal Processing Networking and Internet Architecture
Deep Temporal Analysis for Non-Acted Body Affect Recognition
In this paper, a solution for basic non-acted emotion recognition based on 3D skeleton and Deep Neural Networks (DNNs) is provided.
Exploiting Recurrent Neural Networks and Leap Motion Controller for Sign Language and Semaphoric Gesture Recognition
In human interactions, hands are a powerful way of expressing information that, in some cases, can be used as a valid substitute for voice, as it happens in Sign Language.
