AL
Publications
- On the Effectiveness of Leukocytes Classification Methods in a Real Application Scenario
- White blood cells counting via vector field convolution nuclei segmentation
- Peripheral blood image analysis
- Detection of red and white blood cells from microscopic blood images using a region proposal approach
- Mp-idb: The malaria parasite image database for image processing and analysis
- Histological image analysis by invariant descriptors
- A leucocytes count system from blood smear images: Segmentation and counting of white blood cells based on learning by sampling
- A multiple classifier learning by sampling system for white blood cells segmentation
- Learning by sampling for white blood cells segmentation
- A region proposal approach for cells detection and counting from microscopic blood images
- An Open Source Plugin for Image Analysis in Biology
- A Computer-Aided System for Differential Count from Peripheral Blood Cell Images
- Using Artificial Intelligence for COVID-19 Detection in Blood Exams: A Comparative Analysis
- An Empirical Evaluation of Convolutional Networks for Malaria Diagnosis
- Deep Learning for COVID-19 Diagnosis from CT Images
- A Deep Learning Based Framework for Malaria Diagnosis on High Variation Data Set
- Deep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method
- Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology
- A Combination of Visual and Temporal Trajectory Features for Cognitive Assessment in Smart Home
- Automatic Monitoring Cheese Ripeness Using Computer Vision and Artificial Intelligence
- On The Potential of Image Moments for Medical Diagnosis
- Feature Selection in Mobile Activity Recognition: A Comparative Study
- A novel deep learning based approach for seed image classification and retrieval
- Special Issue on Image Processing Techniques for Biomedical Applications
- Microscopic Blood Images Analysis by Computer Vision Techniques
- How Realistic Should Synthetic Images Be for Training Crowd Counting Models?
- A Shallow Learning Investigation for COVID-19 Classification
- Cryptocurrency scams: analysis and perspectives
- On the Reliability of CNNs in Clinical Practice: A Computer-Aided Diagnosis System Case Study
- An effective and friendly tool for seed image analysis
- Hierarchical Pretrained Backbone Vision Transformer for Image Classification in Histopathology
- 1stWorkshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
- Specialise to Generalise: The Person Re-identification Case
- Invariant Moments, Textural and Deep Features for Diagnostic MR and CT Image Retrieval
- YOLO-PAM: Parasite-Attention-Based Model for Efficient Malaria Detection
- Blob Detection and Deep Learning for Leukemic Blood Image Analysis
- On the Efficacy of Handcrafted and Deep Features for Seed Image Classification
- FIRESTART: Fire Ignition Recognition with Enhanced Smoothing Techniques and Real-Time Tracking
- MTANet: Multi-Type Attention Ensemble for Malaria Parasite Detection
- A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites
- An Anomaly Detection Approach to Determine Optimal Cutting Time in Cheese Formation
- Understanding cheese ripeness: An artificial intelligence-based approach for hierarchical classification
- SAMMI: Segment Anything Model for Malaria Identification
- 2ndWorkshop on Maritime Computer Vision (MaCVi) 2024: Challenge Results
- Gastric Cancer Image Classification: a Comparative Analysis and Feature Fusion Strategies
- Gastric Cancer Image Classification: A Comparative Analysis and Feature Fusion Strategies
- Detecting coagulation time in cheese making by means of computer vision and machine learning techniques
- Snarci at SemEval-2024 Task 4: Themis Model for Binary Classification of Memes
- TECD: A Transformer Encoder Convolutional Decoder for High-Dimensional Biomedical Data
- CRDet: An Artificial Intelligence-Based Framework for Automated Cheese Ripeness Assessment from Digital Images
- Insights into radiomics: impact of feature selection and classification
- Federated Learning for Enhanced Cell Nuclei Segmentation in Histopathological Images
- A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario
- 3D-NASE: A Novel 3D CT Nasal Attention-based Segmentation Ensemble
- YOLO-Tryppa: A Novel YOLO-Based Approach for Rapid and Accurate Detection of Small Trypanosoma Parasites