73 citations · 141 across the 9 of their papers we have counts for
9 papers
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.…
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…
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…
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…
DNN-Buddies: A Deep Neural Network-Based Estimation Metric for the Jigsaw Puzzle Problem
Dror Sholomon, Eli David, Nathan S. Netanyahu
This paper introduces the first deep neural network-based estimation metric for the jigsaw puzzle problem. Given two puzzle piece edges, the neural network predicts whether or not…
A Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles
Dror Sholomon, Eli David, Nathan S. Netanyahu
In this paper we propose the first effective automated, genetic algorithm (GA)-based jigsaw puzzle solver. We introduce a novel procedure of merging two "parent" solutions to an im…