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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

Andrea Loddo's public data