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Found 8 papers, 0 papers with code
Edge2Vec: A High Quality Embedding for the Jigsaw Puzzle Problem
Pairwise compatibility measure (CM) is a key component in solving the jigsaw puzzle problem (JPP) and many of its recently proposed variants.
TEN: Twin Embedding Networks for the Jigsaw Puzzle Problem with Eroded Boundaries
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 latent embedding space.
A Novel Hybrid Scheme Using Genetic Algorithms and Deep Learning for the Reconstruction of Portuguese Tile Panels
Specifically, we introduce an enhanced GA-based puzzle solver, whose integration with a novel DL-based compatibility measure (DLCM) yields state-of-the-art performance, regarding the above application.
DNN-Buddies: A Deep Neural Network-Based Estimation Metric for the Jigsaw Puzzle Problem
This paper introduces the first deep neural network-based estimation metric for the jigsaw puzzle problem.
An Automatic Solver for Very Large Jigsaw Puzzles Using Genetic Algorithms
In this paper we propose the first effective genetic algorithm (GA)-based jigsaw puzzle solver.
Genetic Algorithm-Based Solver for Very Large Multiple Jigsaw Puzzles of Unknown Dimensions and Piece Orientation
In this paper we propose the first genetic algorithm (GA)-based solver for jigsaw puzzles of unknown puzzle dimensions and unknown piece location and orientation.
A Generalized Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles of Complex Types
In this paper we introduce new types of square-piece jigsaw puzzles, where in addition to the unknown location and orientation of each piece, a piece might also need to be flipped.
A Genetic Algorithm-Based Solver for Very Large Jigsaw Puzzles
In this paper we propose the first effective automated, genetic algorithm (GA)-based jigsaw puzzle solver.
