5 citations · 24 across the 11 of their papers we have counts for
11 papers
Using Zero-shot Prompting in the Automatic Creation and Expansion of Topic Taxonomies for Tagging Retail Banking Transactions
Daniel de S. Moraes, Pedro T. C. Santos, Polyana B. da Costa +13
This work presents an unsupervised method for automatically constructing and expanding topic taxonomies using instruction-based fine-tuned LLMs (Large Language Models). We apply to…
Hierarchical Classification of Financial Transactions Through Context-Fusion of Transformer-based Embeddings and Taxonomy-aware Attention Layer
Antonio J. G. Busson, Rafael Rocha, Rennan Gaio +14
This work proposes the Two-headed DragoNet, a Transformer-based model for hierarchical multi-label classification of financial transactions. Our model is based on a stack of Transf…
Building a Noisy Audio Dataset to Evaluate Machine Learning Approaches for Automatic Speech Recognition Systems
Julio Cesar Duarte, Sérgio Colcher
Automatic speech recognition systems are part of people's daily lives, embedded in personal assistants and mobile phones, helping as a facilitator for human-machine interaction whi…
Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset
Luis Felipe Henriques, Sérgio Colcher, Ruy Luiz Milidiú +2
Nowadays, subsurface salt body localization and delineation, also called semantic segmentation of salt bodies, are among the most challenging geophysicist tasks. Thus, identifying…
Prior Flow Variational Autoencoder: A density estimation model for Non-Intrusive Load Monitoring
Luis Felipe M. O. Henriques, Eduardo Morgan, Sergio Colcher +1
Non-Intrusive Load Monitoring (NILM) is a computational technique to estimate the power loads' appliance-by-appliance from the whole consumption measured by a single meter. In this…
A Cluster-Matching-Based Method for Video Face Recognition
Paulo R C Mendes, Antonio J G Busson, Sérgio Colcher +3
Face recognition systems are present in many modern solutions and thousands of applications in our daily lives. However, current solutions are not easily scalable, especially when…
Video Quality Enhancement Using Deep Learning-Based Prediction Models for Quantized DCT Coefficients in MPEG I-frames
Antonio J G Busson, Paulo R C Mendes, Daniel de S Moraes +3
Recent works have successfully applied some types of Convolutional Neural Networks (CNNs) to reduce the noticeable distortion resulting from the lossy JPEG/MPEG compression techniq…
A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers
Paulo R. C. Mendes, Eduardo S. Vieira, Álan L. V. Guedes +2
Discovering and accessing specific content within educational video bases is a challenging task, mainly because of the abundance of video content and its diversity. Recommender sys…
Seismic Shot Gather Noise Localization Using a Multi-Scale Feature-Fusion-Based Neural Network
Antonio José G. Busson, Sérgio Colcher, Ruy Luiz Milidiú +2
Deep learning-based models, such as convolutional neural networks, have advanced various segments of computer vision. However, this technology is rarely applied to seismic shot gat…
A Deep Convolutional Network for Seismic Shot-Gather Image Quality Classification
Eduardo Betine Bucker, Antonio José Grandson Busson, Ruy Luiz Milidiú +3
Deep Learning-based models such as Convolutional Neural Networks, have led to significant advancements in several areas of computing applications. Seismogram quality assurance is a…
A Multimodal CNN-based Tool to Censure Inappropriate Video Scenes
Pedro V. A. de Freitas, Paulo R. C. Mendes, Gabriel N. P. dos Santos +4
Due to the extensive use of video-sharing platforms and services for their storage, the amount of such media on the internet has become massive. This volume of data makes it diffic…