activity
20192025
most citedA Novel Hybrid Scheme Using Genetic Algorithms and Deep Learning for the Reconstruction of Portuguese Tile Panels

9 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2025★ 1 cited

DPDFNet: Boosting DeepFilterNet2 via Dual-Path RNN

Daniel Rika, Nino Sapir, Ido Gus

We present DPDFNet, a causal single-channel speech enhancement model that extends DeepFilterNet2 architecture with dual-path blocks in the encoder, strengthening long-range tempora…

cs.CV2025

A Generic Hybrid Framework for 2D Visual Reconstruction

Daniel Rika, Dror Sholomon, Eli David +2

This paper presents a versatile hybrid framework for addressing 2D real-world reconstruction tasks formulated as jigsaw puzzle problems (JPPs) with square, non-overlapping pieces.…

cs.CV2022

Edge2Vec: A High Quality Embedding for the Jigsaw Puzzle Problem

Daniel Rika, Dror Sholomon, Eli David +1

Pairwise compatibility measure (CM) is a key component in solving the jigsaw puzzle problem (JPP) and many of its recently proposed variants. With the rapid rise of deep neural net…

cs.CV2022★ 1 cited

TEN: Twin Embedding Networks for the Jigsaw Puzzle Problem with Eroded Boundaries

Daniel Rika, Dror Sholomon, Eli David +1

This paper introduces the novel CNN-based encoder Twin Embedding Network (TEN), for the jigsaw puzzle problem (JPP), which represents a puzzle piece with respect to its boundary in…

cs.CV2019★ 9 cited

A Novel Hybrid Scheme Using Genetic Algorithms and Deep Learning for the Reconstruction of Portuguese Tile Panels

Daniel Rika, Dror Sholomon, Eli David +1

This paper presents a novel scheme, based on a unique combination of genetic algorithms (GAs) and deep learning (DL), for the automatic reconstruction of Portuguese tile panels, a…