{"text_format":"2","workbook":"xls","n_sheets":1,"sheets":["report2"],"not_rendered":{"charts":0,"images":0,"macros":0,"external_links":1,"defined_names":2,"comments":0,"pivot_tables":0},"unopened":[],"bounds":{"document_bytes":16777216,"sheet_cells":100000,"run_cost":"one","rows_first":2000,"rows_last":500,"rows_between":2000,"halvings":0,"cell_chars":16384,"cell_head_chars":4096},"cells_cut":0,"cells_raw":0,"read":"whole","date_system":"1900","formulas":"cached_only"}

{"sheet":"report2","index":0,"n_rows":39,"n_cols":5,"rows_kept":39,"cut":false,"hidden":false,"merged":[[0,2,0,3],[0,4,0,5],[1,2,1,3],[1,4,1,5],[2,2,2,3],[2,4,2,5],[3,2,3,3],[4,2,4,3],[5,2,5,3],[6,2,6,3],[7,2,7,3],[8,2,8,3],[9,2,9,3],[11,2,11,3],[11,4,11,5],[12,2,12,3],[12,4,12,5],[13,2,13,3],[14,2,14,3],[15,2,15,3],[16,2,16,3],[17,2,17,3],[18,2,18,3],[19,2,19,3],[31,2,31,3],[32,2,32,3],[35,2,35,3]],"flags":["formulas_cached_only"]}
[null,"1.","Record Nr.",null,"UNINA990005510380403321"]
[null,null,"Autore",null,"Mantran, Robert <1917-1999>"]
[null,null,"Titolo",null,"La vie quotidienne a Constantinople au temps de Soliman le Magnifique et de ses successeurs (XVIe et XVIIe siècles) / Robert Mantran"]
[null,null,"Pubbl/distr/stampa",null,"Paris : Hachette, c1965"]
[null,null,"Descrizione fisica",null,"317 p. ; 21 cm"]
[null,null,"Collana",null,"La vie quotidienne"]
[null,null,"Locazione",null,"FLFBC"]
[null,null,"Collocazione",null,"COLL. 59(23)"]
[null,null,"Lingua di pubblicazione",null,"Francese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNINA9910427707603321"]
[null,null,"Titolo",null,"Pattern Recognition and Artificial Intelligence : International Conference, ICPRAI 2020, Zhongshan, China, October 19–23, 2020, Proceedings / / edited by Yue Lu, Nicole Vincent, Pong Chi Yuen, Wei-Shi Zheng, Farida Cheriet, Ching Y. Suen"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"3-030-59830-6"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XX, 741 p. 95 illus.)"]
[null,null,"Collana",null,"Image Processing, Computer Vision, Pattern Recognition, and Graphics, , 3004-9954 ; ; 12068"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[{"$nulls":4},"Social sciences - Data processing"]
[{"$nulls":4},"Education - Data processing"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Computer Imaging, Vision, Pattern Recognition and Graphics"]
[{"$nulls":4},"Computer Application in Social and Behavioral Sciences"]
[{"$nulls":4},"Computers and Education"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Computer Engineering and Networks"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Handwriting and Text Processing -- Gender Detection from Arabic Handwritten Documents Using the Concept of Transfer-Learning -- Split and Merge: Component Based Segmentation Network for Text Detection -- Gate-Fusion Transformer for Multimodal Sentiment Analysis -- Overview of Mathematical Expression Recognition -- Handwritten Mathematical Expression Recognition: A Survey -- Commodity Classification Based on Multi-Modal Jointly Using Image and Text Information -- A New DCT-FFT Fusion based Method for Caption and Scene Text Classification in Action Video Images -- A New Method For Detecting Altered Text in Document Images -- Hand-"]
[{"$nulls":4},"drawn Object Detection For Scoring Wartegg Zeichen Test -- Application of Deep Learning for Online Handwritten Mathematical Expression Recognition: A Review -- Comparison of Persian Handwritten Digit Recognition in Three Color Modalities Using -- Deep Neural Networks -- Application of Deep Learning in Handwritten Mathematical Expressions Recognition -- Automating Stress Detection using Handwriting -- Recognition of Cursive Caption Text using Deep Learning - A Comparative Study on Recognition Units -- Features and Classifiers -- A Hybrid Multiple Classifier System Applied in Life Insurance Underwriting -- Generative Adversarial-Synergetic Networks for Anomaly Detection -- Multi-Features Integration for Speech Emotion Recognition -- Analysis of Multi-Class Classification of EEG signals using Deep Learning on MUSE Dataset -- A Deep Object Detection Method for Pineapple Fruit and Flower Recognition in Cluttered Background -- A New Credit Scoring Model Based on Prediction of Signal on Graph -- Characterizing the impact of using features extracted from pre-trained models on the quality of video captioning sequence-to-sequence models -- Prediction of Subsequent Memory Effects using Convolutional Neural Network -- Secure Data Transmission of Smart Home Sensor Networks Based on Information Hiding -- Differences and Similarities learning for Unsupervised Feature Selection.-Manifold-based classifier ensembles -- PD-DARTS: Progressive Discretization Differentiable Architecture Search -- Transformed Network Based on Task-driven -- A Blockchain-based Online Game Design Architecture for Performance Issues -- Predicting US Elections with Social Media and Neural Networks -- Deep Learning -- From Pixels to Random Walk Based Segments for Image Time Series Deep Classification -- Handwriting and Hand-Sketched Graphics Detection Using Convolutional Neural Networks -- Deep Active Learning With Simulated Rationales for Text Classification -- License plate Detection and Recognition by Convolutional Neural Networks -- Incorporating Human Views into Unsupervised Deep Transfer Learning for Remote Sensing Image Retrieval -- Overview: Research Progress on Pest and Disease Identification -- Advanced Data Preprocessing for Detecting Cybercrime in Text-based Online Interactions -- A Real-time License-Plate Detection Method using Deep Learning Approaches -- Computer Vision and Image Processing -- Facial Beauty Prediction Using Transfer Learning and Multi-Task Learning Techniques -- CycleGAN-based Image Translation for Near-infrared Camera-trap Image Recognition -- Object Detection Based on Sparse Representation of Foreground -- An Application and Integration of Machine Learning Approach on a Real IoT Agricultural Scenario -- Spatio-temporal stability analysis in Satellite Image Times Series -- Overview of Crowd Counting -- Rotation-invariant Face Detection with Multi-Task Progressive Calibration Networks -- Enlacement and Interlacement Shape Descriptors -- Image orientation detection using convolutional neural network -- Multi-Layer Cross-Domain Non-Negative Matrix Factorization for Cross-Scene Dimension Reduction on Hyperspectral images -- A Comprehensive, Unconstrained, License Plate Database -- An extended evaluation of the impact of different modules in ST-VQA systems -- Computer-aided Wartegg Drawing Completion Test -- Medical Imaging and Applications -- A Novel ECG Signal Classification Algorithm Based on Common and Specific Components Separation -- Sit-To-Stand test for neurodegenerative diseases video classification -- A two stage method for abnormality diagnosis of musculoskeletal radiographs -- Clinical Decision Support Systems for Predicting Patients Liable to Acquire Acute Myocardial Infarctions -- A Novel Deep Learning Approach for Liver MRI Classification and HCC Detection -- "]
[{"$nulls":4},"An Integrated Deep Approach for Lesion Detection in Breast MRI -- Single image super-resolution for medical image applications -- Forensic Studies and Medical Diagnosis -- A Blob Detector Images-Based Method for Counterfeit Coin Detection by Fuzzy Association Rules Mining -- Interpreting Deep Glucose Predictive Models for Diabetic People Using the RETAIN Architecture -- Abusive Language Detection using BERT Pre-trained Embedding -- Classification of criminal news over time using Bidirectional LSTM -- End-to-end generative adversarial network for hand-vein recognition -- A Survey on Peripheral Blood Smear Analysis Using Deep Learning."]
[null,null,null,"Sommario/riassunto","This book constitutes the proceedings of the Second International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2020, which took place in Zhongshan, China, in October 2020. The 49 full and 14 short papers presented were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: handwriting and text processing; features and classifiers; deep learning; computer vision and image processing; medical imaging and applications; and forensic studies and medical diagnosis. ."]