Poster Session II

Poster Session II – October 7th, 16h00min – 17h00min (GMT-3)

Participants with accepted posters should carefully follow the guidelines below to ensure a smooth and organized presentation during the poster sessions:

  • Posters must be printed in A0 format: 84.1 cm wide × 118.9 cm high (portrait orientation).
  • Each poster should be equipped with a hanger or other appropriate mechanism to allow secure and visible mounting on the display panels provided.
  • Poster sessions will take place in the entrance hall of the main auditorium at the event venue.
  • Every poster board will be labeled with the corresponding poster ID and title to help authors locate their assigned space.
  • Posters should be placed in their designated locations at the beginning of the day of the assigned session. This allows attendees to view the posters freely throughout the day, even before the official poster session begins.

 

ID 16 – Decoupled Interpolated Light Field Coding

André Beims Bräscher (Universidade Federal de Santa Catarina)*; Gabriela Furtado da Silveira (Universidade Federal de Santa Catarina); Ismael Seidel (Universidade Federal de Santa Catarina); José Luís Almada Güntzel (Universidade Federal de Santa Catarina)

 

ID 19 – Bit-Depth Sensitivity Analysis of DCVC-RT Quantization

Ruhan da Conceição (Federal University of Pelotas)*; Marcelo Porto (Federal University of Pelotas); Wen-Hsiao Peng (National Yang Ming Chiao Tung University); Luciano Agostini (Federal University of Pelotas )”

 

ID 22 – NNCodec Efficient Dequantization VLSI Architecture

Jiovana Sousa Gomes (UFRGS)*; Sara Henssler (Unipampa); Fábio Livi Ramos (Unipampa); Sergio Bampi (UFRGS)

 

ID 26 – A Performance Analysis of The NNCodec Software Using Visual Processing Neural Networks

Sara Henssler (Universidade Federal do Pampa – UNIPAMPA)*; Jiovana Sousa Gomes (Universidade Federal do Rio Grande do Sul – UFRGS); Sergio Bampi (Universidade Federal do Rio Grande do Sul – UFRGS); Fábio Luís Livi Ramos  (Universidade Federal do Pampa – UNIPAMPA)

 

ID 27 – Traditional vs. Neural Video Codecs: Compression Efficiency, Visual Artifacts, and Quality Analysis Beyond PSNR

Leandro Tavares (UFPel)*; Víctor Costa (UFPel); Ruhan Conceição (UFPel); Luciano Agostini (UFPel); Marcelo Porto (UFPel); Guilherme Corrêa (UFPel)

 

ID 28 – Low-Energy NTT and INTT Architectures for Image Encryption and Decryption

Rodrigo Lopes (UFPel)*; Eloisa Barros (UFPel); Leonardo Antonietti (UFPel); Morgana Da Rosa (UCPel); Eduardo  Costa (UCPel); Rafael Soares (UFPel)

 

ID 33 – A Lightweight I3D-Based Approach for Real-Time Brazilian Sign Language Recognition

Victor Costa (UFPel)*; Leandro Tavares (UFPel); Ruhan Conceição (UFPel); Luciano Agostini (UFPel); Brenda Santana (UFPel); Guilherme Corrêa (UFPel)

 

ID 39 – ASIC-Based CNN Hardware: A Comparative Analysis of 32-Bit Float vs. 8-Bit Integer Precision

Vanessa Aldrighi (UFPEL)*; Denis Maass (UFPEL); Ruhan Conceição (UFPEL); Marcelo Porto (UFPEL); Luciano Agostini (UFPEL)

 

ID 43 – Platform-Independent Hardware Design for Low-Power Neural Video Hyperprior Decoding

Denis Maass (UFPel)*; Vanessa Aldrighi (UFPel); Ruhan Conceição (UFPel); Luciano Agostini (UFPel); Marcelo Porto (UFPel)

 

ID 44 – Machine Learning-Based Block Partitioning for V-PCC Encoding Acceleration

Gustavo Rehbein (UFPel)*; Cristiano Santos (UFPel); Guilherme Corrêa (UFPel); Marcelo Porto (UFPel)

 

ID 45 – Reducing the VVC Transform Computational Cost Through Machine Learning

Caroline Camargo (UFPel)*; Bianca Silveira (UFPel); Guilherme Corrêa (UFPel)

 

ID 47 – CNN-based ISP Decision Scheme

Adson Duarte (Federal University of Pelotas)*; Guilherme Correa (Federal University of Pelotas); Bruno Zatt (Federal University of Pelotas); Attilio Fiandrotti (University of Turin); Daniel Palomino (Federal University of Pelotas)

 

ID 48 – Towards Cross-Dataset Comparison of Convolutional Neural Networks and Vision Transformers for Skin Lesion Classification

Nicolas Raimundo (Universidade Federal do Pampa)*; Eliezer Flores (Universidade Federal do Pampa)

 

ID 49 – An Assessment on Post-Training Quantization Effects in  Handwritten Digit Classification

Érick Radmann (Video Technology Research Group (ViTech))*; Ruhan Conceição  (Video Technology Research Group (ViTech)); Luciano  Agostini  (Video Technology Research Group (ViTech)); Bruno  Zatt (Video Technology Research Group (ViTech))