Andrea Loddo

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