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Found 38 papers, 17 papers with code
CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification
First, for each concept, we prompt the LVLM to answer if the concept is present in the input image.
Second FRCSyn-onGoing: Winning Solutions and Post-Challenge Analysis to Improve Face Recognition with Synthetic Data
In order to promote the proposal of novel Generative AI methods and synthetic data, and investigate the application of synthetic data to better train face recognition systems, we introduce the 2nd FRCSyn-onGoing challenge, based on the 2nd Face Recognition Challenge in the Era of Synthetic Data (FRCSyn), originally launched at CVPR 2024.
Classification of Keratitis from Eye Corneal Photographs using Deep Learning
Keratitis is an inflammatory corneal condition responsible for 10% of visual impairment in low- and middle-income countries (LMICs), with bacteria, fungi, or amoeba as the most common infection etiologies.
MST-KD: Multiple Specialized Teachers Knowledge Distillation for Fair Face Recognition
Our strategy learns a project of these four teachers into a common space and distill that information to a student network.
Evaluating the Impact of Pulse Oximetry Bias in Machine Learning under Counterfactual Thinking
Under this counterfactual design, two models are trained with identical data, features, and settings, except for the method of measuring oxygen saturation: models using SaO2 are a "control" and models using SpO2 a "treatment".
Learning Ordinality in Semantic Segmentation
Semantic segmentation consists of predicting a semantic label for each image pixel.
A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attention
Manually annotating nuclei from the gigapixel Hematoxylin and Eosin (H&E)-stained Whole Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell nuclei instance segmentation and classification could alleviate the workload of pathologists and clinical researchers and at the same time facilitate the automatic extraction of clinically interpretable features.
Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology
The interactions between tumor cells and the tumor microenvironment (TME) dictate therapeutic efficacy of radiation and many systemic therapies in breast cancer.
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition Challenge in the Era of Synthetic Data
Synthetic data is gaining increasing relevance for training machine learning models.
Anonymizing medical case-based explanations through disentanglement
Case-based explanations are an intuitive method to gain insight into the decision-making process of deep learning models in clinical contexts.
Compressed Models Decompress Race Biases: What Quantized Models Forget for Fair Face Recognition
We investigate the overall performance, the performance on each ethnicity subgroup and the racial bias of a State-of-the-Art quantization approach when used with synthetic and real data.
Unveiling the Two-Faced Truth: Disentangling Morphed Identities for Face Morphing Detection
Over time they have become simpler to perform and more realistic, as such, the usage of deep learning systems to detect these attacks has grown.
Ranked #1 on
Face Morphing Attack Detection
on FRLL-Morphs
CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting
Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome.
Unimodal Distributions for Ordinal Regression
We then propose a new architecture that imposes unimodal distributions and a new loss term that relies on the notion of projection in a set to promote unimodality.
Rethinking low-cost microscopy workflow: Image enhancement using deep based Extended Depth of Field methods
Microscopic techniques in low-to-middle income countries are constrained by the lack of adequate equipment and trained operators.
An interpretable machine learning system for colorectal cancer diagnosis from pathology slides
On the internal dataset, the method shows an accuracy of 93. 44% and a sensitivity between positive (low-grade and high-grade dysplasia) and non-neoplastic samples of 0. 996.
PIC-Score: Probabilistic Interpretable Comparison Score for Optimal Matching Confidence in Single- and Multi-Biometric (Face) Recognition
In the context of biometrics, matching confidence refers to the confidence that a given matching decision is correct.
Ranked #1 on
Face Recognition
on MORPH
Causality-Inspired Taxonomy for Explainable Artificial Intelligence
As two sides of the same coin, causality and explainable artificial intelligence (xAI) were initially proposed and developed with different goals.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
OrthoMAD: Morphing Attack Detection Through Orthogonal Identity Disentanglement
Morphing attacks are one of the many threats that are constantly affecting deep face recognition systems.
SYN-MAD 2022: Competition on Face Morphing Attack Detection Based on Privacy-aware Synthetic Training Data
The competition attracted a total of 12 participating teams, both from academia and industry and present in 11 different countries.
OCFR 2022: Competition on Occluded Face Recognition From Synthetically Generated Structure-Aware Occlusions
This work summarizes the IJCB Occluded Face Recognition Competition 2022 (IJCB-OCFR-2022) embraced by the 2022 International Joint Conference on Biometrics (IJCB 2022).
Deep Aesthetic Assessment and Retrieval of Breast Cancer Treatment Outcomes
Currently, there is no gold standard for evaluating the aesthetic outcome of breast cancer treatment.
A survey on attention mechanisms for medical applications: are we moving towards better algorithms?
This paper concludes with a critical analysis of the claims and potentialities presented in the literature about attention mechanisms and proposes future research lines in medical applications that may benefit from these frameworks.
Colon Nuclei Instance Segmentation using a Probabilistic Two-Stage Detector
Cancer is one of the leading causes of death in the developed world.
Myope Models -- Are face presentation attack detection models short-sighted?
Presentation attacks are recurrent threats to biometric systems, where impostors attempt to bypass these systems.
Ranked #1 on
Face Presentation Attack Detection
on ROSE-YOUTU
FocusFace: Multi-task Contrastive Learning for Masked Face Recognition
The proposed architecture is designed to be trained from scratch or to work on top of state-of-the-art face recognition methods without sacrificing the capabilities of a existing models in conventional face recognition tasks.
My Eyes Are Up Here: Promoting Focus on Uncovered Regions in Masked Face Recognition
The recent Covid-19 pandemic and the fact that wearing masks in public is now mandatory in several countries, created challenges in the use of face recognition systems (FRS).
CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance
Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples.
Ranked #1 on
Colorectal Polyps Characterization
on CRC
MFR 2021: Masked Face Recognition Competition
These teams successfully submitted 18 valid solutions.
Tackling unsupervised multi-source domain adaptation with optimism and consistency
It has been known for a while that the problem of multi-source domain adaptation can be regarded as a single source domain adaptation task where the source domain corresponds to a mixture of the original source domains.
SpaMHMM: Sparse Mixture of Hidden Markov Models for Graph Connected Entities
We propose a framework to model the distribution of sequential data coming from a set of entities connected in a graph with a known topology.
Dimensional emotion recognition using visual and textual cues
This paper addresses the problem of automatic emotion recognition in the scope of the One-Minute Gradual-Emotional Behavior challenge (OMG-Emotion challenge).
Deep Local Binary Patterns
Local Binary Pattern (LBP) is a traditional descriptor for texture analysis that gained attention in the last decade.
802.11 Wireless Simulation and Anomaly Detection using HMM and UBM
Despite the growing popularity of 802. 11 wireless networks, users often suffer from connectivity problems and performance issues due to unstable radio conditions and dynamic user behavior among other reasons.
Networking and Internet Architecture
Long-Range Trajectories from Global and Local Motion Representations
Motion is a fundamental cue for scene analysis and human activity understan- ding in videos.
oAdaBoost: An AdaBoost Variant for Ordinal Classification
Ordinal data classification (ODC) has a wide range of applications in areas where human evaluation plays an important role, ranging from psychology and medicine to information retrieval.
Active Mining of Parallel Video Streams
The practicality of a video surveillance system is adversely limited by the amount of queries that can be placed on human resources and their vigilance in response.
INbreast: toward a full-field digital mammographic database
Rationale and objectives: Computer-aided detection and diagnosis (CAD) systems have been developed in the past two decades to assist radiologists in the detection and diagnosis of lesions seen on breast imaging exams, thus providing a second opinion.
